{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6547fb61",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import Lasso, LassoLarsIC\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split, validation_curve, learning_curve, ShuffleSplit\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "791d724c",
   "metadata": {},
   "source": [
    "## 载入数据集\n",
    "\n",
    "以 8:2 随机划分训练集和测试集，以42为随机种子（使得结果可以复现）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ca2b464b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housingMedianAge</th>\n",
       "      <th>totalRooms</th>\n",
       "      <th>totalBedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>medianIncome</th>\n",
       "      <th>medianHouseValue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housingMedianAge  totalRooms  totalBedrooms  \\\n",
       "0    -122.23     37.88              41.0       880.0          129.0   \n",
       "1    -122.22     37.86              21.0      7099.0         1106.0   \n",
       "2    -122.24     37.85              52.0      1467.0          190.0   \n",
       "3    -122.25     37.85              52.0      1274.0          235.0   \n",
       "4    -122.25     37.85              52.0      1627.0          280.0   \n",
       "\n",
       "   population  households  medianIncome  medianHouseValue  \n",
       "0       322.0       126.0        8.3252          452600.0  \n",
       "1      2401.0      1138.0        8.3014          358500.0  \n",
       "2       496.0       177.0        7.2574          352100.0  \n",
       "3       558.0       219.0        5.6431          341300.0  \n",
       "4       565.0       259.0        3.8462          342200.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names = [\n",
    "    'longitude',\n",
    "    'latitude',\n",
    "    'housingMedianAge',\n",
    "    'totalRooms',\n",
    "    'totalBedrooms',\n",
    "    'population',\n",
    "    'households',\n",
    "    'medianIncome',\n",
    "    'medianHouseValue'\n",
    "]\n",
    "df = pd.read_csv('cal_housing.data', header=None, names=names)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7487d08d",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.values[:, 0:8]\n",
    "y = df.values[:, 8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e46b88cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "std = StandardScaler()\n",
    "X = std.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7f564563",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4d56e7f",
   "metadata": {},
   "source": [
    "## Lasso 回归模型定义\n",
    "\n",
    "Lasso 回归的目标函数是在均方误差（ $MSE$ ）的基础上添加 $L1$ 正则化项：\n",
    "\n",
    "$$\n",
    "\\min_\\beta (\\cfrac{1}{2n} \\sum_{i=1}^n (y_i - \\mathbf{x}_i^T \\beta)^2 + \\lambda \\sum_{j=1}^p |\\beta_j |)\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17a87cc5",
   "metadata": {},
   "source": [
    "## 自定义 $L1$ 范数系数\n",
    "\n",
    "`scikit-learn` 中的 Lasso 以  \n",
    "`(1 / (2 * n_samples)) * ||y - Xw||^2_2 + alpha * ||w||_1`  \n",
    "为最小化目标，其中 `alpha` 即为数学上 $L1$ 范数系数 $\\lambda$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7e38a7c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Lasso()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>Lasso</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.linear_model.Lasso.html\">?<span>Documentation for Lasso</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>Lasso()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "Lasso()"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = Lasso(alpha=1.0)\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6396ec4f",
   "metadata": {},
   "source": [
    "## 模型评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5a093709",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "系数\t[-85402.87426904 -90659.07250125  14886.50107984 -17843.5986218\n",
      "  48953.57100285 -43583.42524251  17712.79437987  77010.00708906]\n",
      "截距\t206763.7824940026\n",
      "R2评估\t0.6246554177189154\n",
      "MSE\t4918549105.5521345\n"
     ]
    }
   ],
   "source": [
    "print(f'系数\\t{model.coef_}')\n",
    "print(f'截距\\t{model.intercept_}')\n",
    "print(f'R2评估\\t{model.score(X_test, y_test)}')\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "\n",
    "print(f'MSE\\t{mse}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e4f66069",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hXyCXy1GtVkmn04yNjmE7NlevXiWRSDAyMrJ6NIWqgZwAbXRH4nTQEdNa0uk0H/nIR1haWuLNN9/Etm0mJiYYHh4+9LTebhp8NxIo0zSDURubEAjTMWG9IgbY20iJzWilAY+rMK2Xquvv7+fs2bNEIpFDOYcjZYvUnUJRq9XILeZYyi8RDoXJZrOcPHUS0/CNUw3ToKenh+npad566y06OzsZGRm5+/6pBsjby+K0s6XgsBfUrq4uhoeHyeVyTE1NcevWLU6dOsXg4OChnctenCc2K5IIBOpeAmE6Qg56pMRWHBdhWtlk20rVzc7OYlkWvb29PPjgg3R0dByokeyxYYvUneM6LOWWyOVyWLZFV2cXZ8+eJR6PI7j3dRiGwejoKH19fUxNTfHaa6/R29PL0PCQ7/ytmivEaWsn8MOOmNYeOxqN8vjjjzM7O7vK5qi3t/fAz2k/LJFWClQw7n1jAmE6ZFbuGx30SImtOA6zkFrkcjkKhUI7VTc2NrbvqbqtOOqISakmrjeHIexVEiOVpFwqk8vlKBaLJBIJ+vr6yHRm0LXtvT/hcJhTp04xMDDA5OQkr7zyCoMDg/QP9KPr1rI4jW0pTkf5HrW+J0IIBgYG6Ovr486dO7z77rurXCQO6ju0n159gUBtTiBMh0TLGiifz6/aAD1qn7qjEialFOVymbm5OZRS3Llzh4GBgQNJ1W3FUafyhBBoehVX3kLTwFaCkBDYTcsvZMjlAMhms1y8eHFP708sFuPcuXNUKhUmbk8wNzfH0NAQPb29eOomuj6GJrYe8ndUEdPK42qaxsjISNtF4vXXX2/7HWYymX0//kGYyK4UqNa490CgAmE6UNYbKfHmm29y+vTpA72z2y66rh+6MK2XqtN1nYsXL9LR0XGo59LiKD8HpSSunMYM5VGM4Uko5PPkFpew6zU60xnGxsZIpVPrpup2SzKZ5OLFi+QLeW5NTHJrZpqRkWGyWQ/TOIEm1he/o0zlbdRgq+s6J06cYHh4mNu3b/Pyyy/T2dnJmTNnNnSR2O3xD3IeVGuabkugVhrFHvVacdgEwrTPbLRvtLIb/Kj7MVocVirP87x2A2yhUCCTyaxK1eVyuSNPo8HhR0xSNfHkFFLVAJicmCRfyBMOhfyREadOEg+FOajaMwV0ZDq5L93B4mKO27dvMzMzw+hoiWzXQ2ji3n6wo95j2kwYTNPk9OnTjIyMtF0kent7OXXqFPF4fM/HP4yxGysF6sM87j0Qpn1gJ6PIdV3H87wjPNu7HGQqr5Wqm52dZWFhgVAoRF9fH+fOnbsnFXVcvOoO8xw8WaBpT7KUW2RxMdf++bmzZ4nF4+3YyFYeptDZ8U7bFuuXAlxAIhFCo6enh2w2y+zsLFeuvMN04g4nxj5OKrXa/PU47DFtRTgc5vz5820Xieeee47BwUFOnjy5pzToYTpPfNgFKhCmPbCbUeRHkT7biIMQJsuymJ2dZW5uDtu26enp2bKq7rhUBx7Gout5LkuFd8nlbrQLGXp6e5icmGRkZHjdYg9HebAbcdoAqQQu3j2F6JqmMTg42C4xf+2NPyKduo8TJx4AI4yp3/38jiqVZ5pbVw62iEaj3H///eu6SIRCoR0f3/O8Q++darV1gD/ufXFxkUQiQTKZ/EDPggqEaYdsNlJiO3cymqZ94CKm9VJ14+PjZLPZbXvVHXUq76AX2nq9zuzsbXL5NxGaS7arq13I4LoukxOTm/79foiTUuAh8Nj8+jNNk7GxMfr7+3nlym1+40/mEZFB+vt6GEqFceTR3K3vNgWeSCR46KGHKJVKXLt2jWeeeYaxsTHGxsZ2NKH4MCforqT1mjVN49q1a4yOjhIKhT7Q494DYdoGOx0psRkflIhpvVRdf38/58+fb5tubpfjIEyw/2kqz/NYWFhgdnaWSnWa7h7FiRNDdKRSuypj2Is4KdVK3W3/pqhoQ0lPMzhqk88VuHalyM14iogFUio07XAFaq97s6lUiscee4x8Ps/Vq1eZmJhoj97Yzg3UUQlTCyFEO6XX+vfKFN8HSaACYdqAtaPI96vf6P0eMTWbzbZXnW3b+9IAu9VsqLrtMVNqUrNcYiGDgVSYeHh/L939EseVgj0/P08kEmJgUOfshWHMHdydb8RuxGmj1N1WTObruJ5ksCvBYBcUy0mu3Syz0ITXrtzkobPjh7oY7pcwdHZ28sQTT7C4uMi1a9e4ffs2J0+eZHBwcNPnP2phap3Dypvh9fagjvoc94NAmNaw2UiJ/fjA34/FD57nsbi4yNzc3K5SdVuxWXXgUs3mq7cKLFRsNCGQSpFNhHhyPEM2sfN9gs3OYS/Ytt0ug282m/T19fHQQ+eJxovA5l53Oz22L04G+jakxlVbp+7Ww5OSSsMhtuIGIN1R4fyZNHOX57l2+w7VxWnOnDlzKK4LsL9jSYQQ9PT00N3dzdzc3CoXib6+vnWPcxyEaeU+11qbo9Z69UGYphsIE/s/UmIzdF3Hdd19e769sJkwrb3zD4fDu07VbcVG0YpUijemK+SqNqOd0bYw3Sk0eGO6zP9zpgttHxeqnUZMUkry+Tyzs7PkcjlSqVTbXBZRxpOzwMGkbR3lbho5KSVw1M5SdyvRhCASMig1HFZ2AgnmSISrPPXEx6CW59133+XWrVtt14WD5CAGBQoh6O/vp7e3l+npad577722i0Q2m111vOMiTGtvBtczin2/j3v/0ArTQY6U2IzjnsprpepmZ2dxHIfe3l4efvhhksnkgb4n6wlkpekyV2piahqXJ4vk6w6GrpGJmlRtj4eGOuiM71/UtF1h8gsZZpmdnW0vbKdOnSIajaKUxJMzSFnct/PaCEd5KKHf8yX2AA8PfQ8NuUIIRjJRXqlalBsOybCBIxULFYf+VJHuZJlI5zD9/f1MTEzw6quvkk6nOXv27LpNrUopCnUHx1OkogYRc/XiWrVcbizUmCzU0YVgPBvnRDZGeMXjDrJcW9M0hoeH25ZNb7zxBolEgtOnT9PZ2dle9I9amDYb7PlBEqgPrTB9//d/P/39/fyTf/JPDtWn7jgWP7RSdbOzsxSLRTo7Ozlx4sS+peq2YqNoxZWKq4tVrszXWKo6uFISMXU6owZdyRDXFmo8Mb4/wrRVxNQqZJiZmaFcLtPd3c358+fp7OxcMUKkiaemUMral3PaDq7yAB1DtP4/uHj7ci0PpiM0nSQTS3XmKhaGptGXNMEFQQ7XA8PobxcQ3Lhxoz0a/fTp0+2BjaWGw+XJInfyDRxP0Rk3Od+f5GxvAiEEddvjK9eXuFNokIgYSKV47sYSC5UmT53swtTvDrU86O+oruuMj4+3XSQuX75MJpPh1KlTAEcqTK19762+kxsJ1PtpFtSHVpiazSbz8/OHfidxXCKmlvV+a7REK1V34cKFfU/VbcVGopCv2txcbJCvOyTCOrFQiLLlMluxiUdMpopN7rc9YqH92edaSyudOTMzw8LCApFIhIGBAe6///57+mBsWaThLRLCRd/l5bTb4gsXD+npoCnkPqYOhRCc6kkwmIlSszwMHXTX4r2q/wI9mQM8DH2IUCjE+fPnGR0d5fr16zz77LOMjIwwPDrGX10t8NpUqZ2Km69ozJctIqbOWFeMyXydqUKDsa4Y+nKln+1KbubqjGfjjHTGgINJ5W2EYRicOnWq7SLx4osvAtBoNA79+9GitW5sVxw3G7Vx3AXqQytM8XicarV66B/OURc/rEzVWZZFJBI58FTdVmxUlffefBVdF0QMDduV1BwP21XYjkehbjOxVKPUcPZFmOCuMLQKGWZmZtqVhxu9R0pJGnIeR5b9v1UaIUAXh/cZe2hYQmAg0A9gTytq6kSXU2qVirXqPfBkAQUYmj8XqTUafWxsjKtXr/I/v/QVLhXjRKMJUnETDUGl6VKsO7w5XWKsK8Zc2SJq6m1RAggZ/jWRr9ltYTqKVFooFOLcuXMMDAzw/PPP8+KLLzIwMMDJkyfbEeFh0cq07DSLsV4Eddyn6X5ohamjo4P5+flDP+5RpPLWS9WdPHmSWq1GrVY7MvPUFhtV5dVtF01A2NDINy1cJQgbAtCo2y63lhosVCz6U/vjRl4sFpmcnGRpaWlbozc8ZVH3ZpArJ8yKwxUnFwNHCoQAR4ESBgYHWVyzdqAjNL0Kmpompt8d2tfR0cFjjz3G7Ms3WZi4Rb9dQxmdxJIdxMI6t3J1buVqSKkI6QJ3nc9fQjuN5x/r6DwmW44TTz31FDdu3ODZZ59leHiYEydOHFoEtdOIaS3vJ4H60ApTK2I6bA4rlaeUolQqtRtgI5HIPam6qampY7HftV4qTymFp2CpauN4irqjEELiSb8yz9D8O+/JQpMHh1K7PnatVmtHj1NTUwwODq7aH9kIWxZpeouo9SKUtjgJdHEwIqGUwBEGUsHK9cRVAjAwD1AU23tqSsNGAwRSVqlzZ1mc7i6csUSCrs5OOmNQLBYoFot0dXUhlUIpgaYJhjNRri1WKTUcUlETpRRLNZt4SKev4+5Nx1EWH7TSiIlEggcffJByuXyPi8RO7JJ2Q6tUfK8C8n4QqA+tMCUSCWq12qEf96BTec1ms+1Vt1VV3VaNrYfFelV5i1Ub21MMZaLcXmrgKYWUCqkU8ZDOaGeUsKHz3nyVb7rYs6Mvk+u6bUeGViFDOBzm3LlzW5Y8r03dbYhYnquEsbU47XAhkOg4CDb66FwEKONAvtxK+Qubq3Qcpa0WRVmjpu4QN4ba4tTXESEVM2ko6OodpFGvcnNmkbqn8fGRBACD6SgPDqZ4Z7ZCvuZHn8mwwaMjGbpW9Kod5h7TWtaWind0dPDoo49SKBS4evUqk5OTnDhxgpGRkQMrGNpO4cNO2EigTNM88lEbgTAdMgeRytsoVZfNZje9wzwuhRhrIybHk1xdqFGzPL7hXDdPX89RbjqYmkDXNPpTYS70JZmvWHieomJ5dEQ2v5TXFjJEo1H6+/t54IEHME2Tr371q1ue57qpu01f2A7EaZusTN1thofAQcfc57SelApbmbho656Dp+rU3EnixjBC6AxlojwwkOJmroYjJVooSl9fGMNtwNItLl8ucebMGR4cSjGcibFUs9EEdCfDpKKrI5CjTOVt1MOUyWR4/PHHyeVyq1wkhoaG9j26W6+HaT/YrEjiqATqQytMyWTyfZ3K206qbjvnchwippXCNLXcPPvObJWpfAPL9bg40EGx7uJ4/h1zxNCYKjYRQGd88/SJbdvtnqPNChm2KhffNHW36YsDG4GpdIw9pNeUErgYeGw/wPLaab39ESeJRlNuXV7hqSbVZXFKRU0+cbqLeFhnrmzhSUlXPMxDQyOMZULcunWLS5cutXvBunoTGx//GEVMKxFC0N3dTTabZX5+fpWLRH9//76d80G7m68UqKMe9/6hFqZarXbod2F7jZgajUbbq85xHPr6+nZdVXccxk20zkMpRa5q88LtIo4rGe2MUm665Ko2lisZyUS4U2wyX7UJ6wLbk2iaoNp0sRwPVkRMUkqWlpaYnZ3ddiHDRu+dUh4NubB16m4LnOW9mN0UJkg0nG0ZEN2Lh0ApExNnpxnDNc+jY0uBYnsWSlJZy5HTCMOdMXqSYRaqNihFJh4isWx11Coxv3btGs8++yyjo6OMj4+vO5biqPeYtjq2EIK+vj56enqYmZnh6tWrbReJ7u7uPa8z+53K24jjIFAfWmE6qlReaxHeib1Jq7lzbm5uR6m67ZzLcRCmllPyVKFBteky1hVDKsVoZ5TJQoOZokU2GUIBIU1jKB0hamrEwwaRkM7lyRJffy6L3Wy099dajgzbKWRosTZi2nHqbgscJWCTqrn1hGe7qbvNkICDial2Lk5K+X8ruRupbXdhksqm5k4QN0YImybDmfU/h1gsxoMPPkipVOLq1as888wznDhxgtHR0VUL8XFM5a2HpmkMDQ21XSTeeustotHonm2bDnse1EqBao17PyyB+tAK01Gl8lpftK0udKUUxWKRubm5XafqtuI4CZNSikrTJWz474kmBCeyMVJRk/fmqgxmwsRMHcv1yMZDxEI62UQYXUiuzSyiFSYIuTWy2ew9jgw7OYcWu07dbcFW4tTCFwQDyc5FyfM8CoVCe6Ac7E6cJAJ7zRKxYz9B5VBdFiddbO7SkUql+MhHPkIul2uPpTh9+jQDAwPta/WoIqbdRGuapjE2NsbQ0FDbtimVSnHmzBlSqZ1Xkh7UHtNWCHF3mm5r1AbQngl1EAL1oRWmRCJBo9FoW3UcFq2Le6PjtlJ1s7OzuK5LX18fjzzyCIlEYt8vgOMiTK3zSCdNbi7V23fGmhB0xU0SER3XkyxWLHRNkAhL0iHF0sISpWKJgmfSMdDHo2ce2nXJ7t0xAvuTutsMRwmU8NNr67Gb1J1SilqtxsLCAoVCgUgkwsTkBJl0htHRUSKRyLI4GZjK3UbxhO4PBFzzOIXacmz7vefmUnMmiJvD6GLrnrNsNktXVxdzc3NcvXqV27dvc+bMmWO7x7QVhmG0bZtu3brFiy++SDab5fTp0yQSG++prXcORyFMLVoC1Ww2+au/+is++clPYprmgYx7/9AKU+tOslqtkk6nD+24rRB4ZQFEa2Ty7OwspVKJrq4uTp06tedU3XbO5TgIUytaGe2MciNXZ6rYpCtuohTczjco1l0y0Qg9SZOpxTLv5Ze4KSQPDXfQMzRKjx7i3Hj3nvpIhBD+pr03gVTrC8Z+4ioQ60ROLjqOXL/ibd3ncV1yuRy5XA7btunKdnHu/DkS8QSe9JiamuK1116jt7eXoaEhTNPcNHLyBwoaeNwrSi3ELsxhFR41Z4q4MYyubS1OK12/p6ameOutt/A8j0qlsq5J7EGzH9FaKBTi7NmzjI6OcvPmTZ5//nn6+vo4deoUsVhsy78/qohpLa0bhNakhIOYBfWhFabWnUqtVjtUYYK7vUyFQoHZ2VkWFxfbqbqLFy+uu/F7EGw2B+kwaQlTKmrysRMZ3p6tsrhsfRM1BEndhcoidr6M8MLEE3GUZlIz4uhS52JfnHRsb82NrqjRUDYx1blPr2prHCVQGOjCQQGOMtDU1qKklKJcKZNbzFEsFonFYvT19ZHpzKBrdxeucCjMqZOnfAfw2xO88sorDA0N0dffh9JMQspFiLtxmVpO3W0Wqe1ln0fhLVfrDWFoWy/E4N88jY6OMjg4yF/8xV/w9ttvMzc3x5kzZ3YUbeyV/dzfiUQiXLhwgbGxMa5fv85XvvIVhoaGOHny5KZp+sPeY9qIVjNuazRQ62f7KVAfWmEyDINoNHro+0yNRgOlFK+//jpKKXp7ew8sVbcVRxExlRoOFcslYuh0xk205Yu7tXfRkwyTTYRYyJdZWJjnmYk5bEcQ6e/ksYsD1D3BTKnJzVydsKHx5IlOTmS3t8ith1SSipujqVfxZGa/Xua2cRF4nomtdDwFm32dbccmt+hHR57n0dXVxYULF7Ys7ojH4ly4cIFiscjtidvMzc0xMjJCdzZLGA8hFJ7Sl/e/tjjhPXcXSO6UbzBbyLBUMUhGDE5kYwxlopte/61I4fHHH2d6eprnn3+egYEBTp06RSSyP5ZUm571AexvtXwFx8fH2y4SrarE9aL/o07ltVgZubU+s5VbFJ7ntfefdsuHVpiEEIdmS7Q2VSeEYGBggLGxsSO9A2ptaG50F1ysOxQaDoYm6E6E7pmhsxMcT/LanTK3cnXqjkdI1xhMR3h0JNWO3FqODNcnZ1goVunNdnLf6TFuV6CvKw5ACOiIGIR1ja893cmpnvjuz0lalNwFPOUihMBSOlJpaOLwxNpTOpYSWHL9iK/Vr7a4uEipVCKZTDI0PEQ6nUYTO7t20uk0D6YeZHFxkYmJCWZnZxkbGSGdSiHFNkSJvVfG5aoWr06VqNs5wvoAS0sRJvN1HhtNc75/a8/GcDjMhQsX2iXmrcX8xIkTB2oJdJCFF8lkkkceeYRisci1a9d4+umnGR8fZ3R0dNU+9HGLmFaydqDiXvnQChP4fnkHVTLeqqprpepaTgMXL17ktddeo6Oj48gvsrtzhFbfiUmleHOmwpX5GjXbRSDoipk8MpJiML27u9P35qu8NVMhmwjRkwzTdDxu5vxCh37qVCoVnnn2OWbsEDUjhZHsxpI6SWkQ0l2mCg264iGUUizWHAbSEQY3KD/eDnWvTNXL31NlZiudEBy8OC1X3XlKAyHx0HCUQWtptWyrHR0ppchms4yMjOy5IlMIf6R4V7aL6elZXn3nBul0ilNjg8Rj23s/tyNMtuuRrzsoBamoQSxkoJTiVq5Ow/EYSEeAPMR7KVTDvD1TYbQrvqFTfGuxa31n4vE4Dz30EKVSiStXrrRLzA/KEugwKgLT6TQf+chHWFpaalcltoomWo35h5Xm34yt9rr2oxDiQytMLUPGSqWyr8/baNztpfE8r52qW7lhe1ysgFpftLXCNFVo8sadMh0Rg55Ov6dormzx4kSR/1c0226O3C6t2TqpiEFy+W91IdHtMs+/PsHFlEtX3KRj5CyTiw79sRDJsI7tKWZLTZIRP+WTrzlomuBENsr9Ax3tUQw7QSpJ2c1hydU3JHfLxcWyOAm0AzJClQgcDJRa/eW1PUV1qUpxyffw6+joYGRkhFQ6tePoaEuESc/gOOmeQe7cucNLr73NcF8Xw0ODmy5+Sm1dlTdfbvLuXIVyw0WiiIcMTmZj9KUiFOo2HRFffl2l4ZAnGe9kZkmnULepWRrTxQYNR9IZDzGciRIL6e0biLULXqvEfGlpiStXrqwqMd/P1Phhlqp3dXXx0Y9+lIWFhVUuEsel+OEwzuNDK0ywf02261XVnT59mq6urnUv5uMyxXalMK3k9lIdIUTbq0wTgr6OMBP5BnNli1PdOxQmT2K5iqgpKJVLFPIFypUy8VicjnQnI6Nx7NIicw1BPGS0fe/ChqA/FSFXtXjqRIZYSEcq0IU/r2enrEzd3YMQ3HVFFe3RFfstTt5yw+zK1b3ZbALwzjvvousavdku7h8bJRw6mHEKrjL8/STANEOMj5+gr6+PyYkJXn7lVUaGBukf6F9VSNFCbbHJVLNd3pop03QlPR1hBIrposWX3l2kLxWmWHfIxE1CZhJvub6vqZYQepzpQoObuTo128XQNRxXMpCK8LFTXUT19YWp9bNWifns7Gx7Md8vxwU4XGEC/zX19va2XSSuX7/edmA4ykZj8Ne7QJgOkL3sMa1M1S0sLBCLxbZdVXdcIqaVqbyVNBxvee7RXbTlx7rezne/pd2kVsxxdbFAV1SjM9NJX38/M1WPUqnJq7MNRMNFpG06Y6vfu7Ch4UiFKxV3ik3euFOibktSMYPxrjj39Se2tfdV98pU3KUNf39vCfSyOAnQ2A9vQ/Awl8dSgJR+VebiYq59DY6MDNPZ1YVALFfL7W/ZesvFYb2PMBqNcfbceSrlEjOTN5ibn2NkeGTdhX2zcvHFqk2+5tCVMGnYkrlSg6lCg5rtoQGehMmixYMjETKxEFIqchWLRMzjZkEAScaz/r6hlIpbS3Xem6vw0ID/s83EobV329fXx+TkJG+++SaJRIKzZ8/uufL2qJp7hRAMDg7S39/Pc889x/z8PJVKpe0icRQCtZ3ezyCVtwd2EzHV6/W2V53nefT19fHoo4/uqLfiuERMrXLPtefSmwwzW7LIxu/emVmuxNAEHdHtXTKtQoaZmRmq1SqDsU7c3j7iiTiJsMGVXI3ri3UGUxGU0Jgqe+iqieVKkpG7ZcAVyyWka7x4u8hXbxWwXUkibJCIGCxWbBqOx1MnMm3hXMtGqbv1uNfVQGBLjZC2N3FSy6k7qQSNZoPFxUVyuRymYdLd3c2JE+O8/vobJDs62ou+pwQOJgb2/tzxK4GtNi8FB0h2pDh738OUl+aYnLrNzOwMY6Nj7YV9o7t1V0oKNZs3popcX6wwVzLJ132Riph+Cfx81eWBkS6q8zWuzdcYyHhoQpCOmvR1hHlvbonhDh3wI0VNE3TFQ9wpNLjQ4+9tbue9WOm4cOvWLV566aVdNbSuRCl1pGk0TdMIh8OMjY3hOA6vv/46yWSS06dPk8kcbjVpkMo7YLZrS9RaZOfm5iiVSu2LfKNU3VYc9Xj1lawnTCeyMe4UmtzON0hHTVypqFgOp7vj9CQ3Ti+1KshaoyXi8Xi7SdIwDG7nG1ydr7JQtVmqOZzriXOuL0mtWsGOQjNisFCxSIT9dF6p6VJpumQiGq/eqaBrcLI7jiMl+ZqDqQtuL9U507P+eW2auluDv8e0+mdN18NyJWFDoyOk70qcpNJpurBUyJFbzFGv18hkMpw6dco33kUg1fo3Ka4SKBHCVHsTp5Wpu20hBKlsH11dXczPzXDlyhWSySSjY6Og7hWHUsPhnZky13M1ri1UqdkeTUfSsD1sVxILaUgRwlIac2WLc30Jik2H871JEhGDbCJMse77ETqUEECI1Ytt6xrdyftgGAanT59meHiYGzdu7KnEXEp54IMAt8LzPEzTZHh4uO0i8fLLL9PZ2cmZM2cOrfF4s1Tefk0r+FALUyKR2FCYlFIUCoW2V91OUnVbcVxSebC+MKWiJh87meHaYo3ZkkXE1LjQl+ZUTwJDu3dhsCyrbaNk2/aGUeR4V4yRTJQbuRq2KznRFWtX8AgE451RFqs6IUPw9myFxaqNAKqWi+VIBjJRFqo2pYaDJ31vPV0T1Ox738utUndrWT3wTnJ9sc5MsYnlSSKmxlAmwtlslJC2vc9NKSjXbeYWciwtLREKhenu9m9oNiu1XYunBOxSnKTy97TcnYhS6/wRuMKkb2CInp4e7ty5w5tvvEk8HkesuAZcKXlrpsRCxcZxJb3JMPm6w518g0RYR9MECzVBT4dGb0eEquVSd1zSEZPxbLy9V5iKhUhGdAoNl654GVDoMkO+ZnP/YAeGJnadSotEItx3332MjY1x9erVVS7m2xWbo/Tpa7GyXNw0Tc6cOdN2kbh06RK9vb2cPn16Wy4Sez2PzapD9yPC/9ALU6FQWPWzVqpudnYWKeWuUnVbcVxSebBxk206ZnK6O85oJko6Zt6zj9MaLTEzM0M+nyeTyTA+Pk42m133bqrcdJnK11mqOdQdScOR7UIGoQkUCk8q0jGTqOEntEKawPb8cRgVy2WhapOJmcTDOo6nmK3ZaJpgpVbuJHW3ltbG/tWFOtcXq6QiBpmQScPxeG+2igDO98TQNzFg9TyPpVye6cUijWaTTKaTM2fOEk/Ed2XlA744KUKEdpDWkwhcZe6pH1YhcJRByIDx8XH6+/t578p7NKoNJicnGRgcIF93Wao6ZOMhZktN6paHlAqFomIrDN0EAZm4STSkU7c8Sk2X8WxiVQFLxNA43ZvknZkKd4oNDM3Cc2sMpfo535dEedaeF7x4PM7DDz9MsVjkypUrTE1NcfLkSUZGRrYUnePQQ7Reg204HOb8+fOrXCQGBwc5efLkgTUeu667pfgFe0x7IJlMMjU1RT6fp1KpkMvlKJfLZLNZzp49S2dn54FcjJqm4TgH78e2HdYTpkLd4dWpEnPlJq6ETMzkvv4kJ7IxarVae/Ceruv09/dz5syZTd0H8jWb524WyFVtTE0wXbK4ulDl6kKVR4c6SBoK25UUmi79HWFmi02kgkjIoC9qIJXiynyVctMBAeWmQ9OReFKxWG4yU7QY7YztKHW3lla5eN1xmS01SUcM4sul7aZuoBTcKTQZycSIGzr6imq9loHq4uIii7kiejRBd3c3XZ2d6Pr+fMUkAkeFtjVXyXdx0NlF4eI9KMBSBiE8IpEIPd095PN5SqUSCwsLmOm+5YGEUGzYlOouyYiBaYSoOIqBpInrge0qZpaHO45mYpzsvrcxeigdJRHWWSzbNF1JR9RgJK1IRgwqlca+fRfT6XR76uyVK1faJrGbDfU7bhHTWqLRKPfff/8qF4mRkRFOnDix771PWxU/BBHTHpBSMjMzw1/91V9x5swZfvqnf5pPf/rT3H///QfexHac95gsV3LpZp5352tULYdCzaXuOPzf1+9wf9pmJGwxNtDNfffdRyaT2dZF+O5claWqzVA6wrUF3wdPE4J81eHSrSIJE6KO4sHuGImQwc3FGg3XIxM1EULQGQ9h6BqeUm2HcU1odIQ1hKbxwu0Cp/sVnlbCdj2ariRkaESMHWzQLpeLW47Ecj2S8dWpimhIo9z0U4qhZbFRnsXS0hKLi4vYtk0q08up8xeJxXbvRrEZraF/oQ3ESSm1PDtp/yu1bKUTXj6GYRqcPXOWpfwS716fYLGgqCTTaAiipo4lDUKmRlR4LFUdxrMxupNhPKm40J/k4ZE0rqeoNl0iIQ1jxWKbjoZIR1d+/xoUnTmEjOxrBdrKqbOtoX6tEvNsNnvPsY6LMG1VdJBIJHj44YcplUptgRobG2NsbGzfpigcRvHDjt/p6elp/v7f//t0dXW1Vfrll19u/14pxec//3n6+/uJRqN88pOf5Nq1a6ueI5/P85nPfIaOjg7S6TSf/exn79nreeONN/j4xz9OJBJheHiYn/3Zn73nXP7gD/6Ac+fOEYlEuP/++/mTP/mTVb9f71y+/OUv8xM/8ROMjY3xX/7Lf0HXdf7kT/6E7/7u72Z4ePhQOquPcypvrmzxwu0i786UeWWiwJtTBa7NFLmZq/FWMYTbfYahE2e2Pe+o4XjMlS064yFmShavTJUpNJzltJliMBMhHTXoj8HHTnSSivqVY03bo2y52K5HKmqSCOkg/f6l7kSYwVSYno4wtuuQa85zszjLzVyN524VeO5mgedvFHh3rorjbe99bqXZwqZG2NBpOqujrobti13YEJTLJa7cuM0rr71FPp+nt7ef8w98hMHR8b2J0jY2jiUCW5n3PNSfnRQ6EFFqYSkdT2rL5eyCbFeWpz7yEKf6O7k+vUS1WiVkhmi6CqEJBtMRelNhelNhzvUm+IYLvVwcTPHeXJWvXF/iKzeW+OqNAneKDTYz4bNknZI3v+NxG9uhVY798Y9/nMHBQd544w1eeuklSqXSqscdB2HaiVdeKpXiscce45FHHiGXy/H0009z+/btfbkh3qqPaT9uIHb0ThcKBT72sY9hmib/9//+X9555x1+7ud+blW54s/+7M/yy7/8y3zxi1/khRdeIB6P86lPfardRAjwmc98hrfffpsvfelL/NEf/RHPPPMM3/Vd39X+fblc5hu+4RsYHR3l8uXL/Jt/82/4yZ/8SX7913+9/Zjnn3+ev/t3/y6f/exnefXVV/nmb/5mvvmbv5m33npr03P5tm/7Nt58801+7dd+jV/5lV9haGiIxx9/fFdv3m45rsUPlit5dWKJVyeWmF0q02jYJMKCTDKGZobxNINc3eVmrr795xf+oLtS0+HSrSVmyhaO55eeC+GPRu+I+JV/hiaIh3QqTZfJQpO3pytcXahybaFKPKwTMjSSYR1Tg7rtMV+tU9MKFOwmt5YavD1bRUnIRE10Da4t+unC7aKUImYa9KciFJsuVcvF9RTlpkulYRN1q7z37tvcuHETwzQ5feF+Tp67n2RXH2KdZtSDYq04+WPPty4F3w9sNOSKRIuu6Xz84hiPnBnDFWHmlop4dpPumMHZniTn+zp46kSWx8Y66esI8+5smesLVQxdkIgYVG2XN+6UmStbmx7X8hpYZhGpDuZ7o+s6Y2NjfOITnyCdTvPiiy/y2muvtdtJjlqYWlOvdxqpdHZ28sQTT3D//fczPT3Ns88+y9TU1J5ujA9jht2Onv1f/+t/zfDwML/1W7/V/tn4+Hj730opfvEXf5Ef//Ef52/9rb8FwH/+z/+Z3t5e/vAP/5Bv//Zv59133+VP//RPeemll3jssccA+JVf+RX+xt/4G/zbf/tvGRgY4Hd/93exbZvf/M3fJBQKcd999/Haa6/x8z//820B+6Vf+iW+8Ru/kR/+4R8G4Kd+6qf40pe+xK/+6q/yxS9+cdNz+fZv/3b+5t/8m/yv//W/jmyK7XGKmDzP4/K1O1y6MstLU1WWajqZmEFEN0gtj5Ooly3qtiRq6syUmjw8vL0JnGFDIxM1+Iv3cswULTSgbnkU6i5dCRPT0MnVHPqWix/enq3QETE41xvj9lKDpZqLwKUzbtLTEfKLJ2wHw7QJxfxFY6EKN3I2IxmTVPTuvpBAMFuyGe10t7RRWlkufro7hgBmSk2m82Xseo2YqtPRnaBvcJB0JuOXeWPQ8ASGkOh78NbbTVFES5w08IvYD6nP0m/S1fGUv8+mlAItxJmBDO8sNghFIuhug1IxzyvVBr2dSfI1i2LDRkrF7aUGvR3h9qTiSCLEfNliMl+nryO84QtRSoHuUXBmyZj9aOJgbgRa1W4jIyNcv36d5557jsHBwSMvfmjdyO7mHFr+iN3d3czNza2yOerr69txhLNZKm+/XCl29Cr/9//+3zz22GN867d+Kz09PTz88MP8xm/8Rvv3t27dYm5ujk9+8pPtn6VSKZ544gkuXboEwKVLl0in021RAvjkJz+Jpmm88MIL7cd84hOfWJVW+9SnPsWVK1faVXSXLl1adZzWY1rH2c65JJNJarXavtXeb5fjEjHVajUajQaX37nBn792G80Mc/HEAB2xMJYUVC0Py/VoOBJdF4RNDalUe1HZLrquoZSfhhMCLE8R0v3l2PUkTVfSFVEsVm1myxZnehN8/FSWb7yvh4+OpxjPxsjEQ2RiIWzPQ0QqhON1QrqGq6Bme9xcatL09FX+c9GQP4rdcrcWjZXfJeU5pGSJZO0OvTLP4yMJPvXERS6cP0dnZxdCaLgrXBxcpflmrIeIAixp0PCMdTOAB+cIoBCArTRsT8eSJndKFq9PFak0HEBDjyZJpTMo6XJzJsflG7NMFxq8NVPhdq52T3o1FtKpNl1cufH3UCmJQOBIi7wzs6sCl50QiUS4ePEiTz31FLZtU61WmZubw3UP9rgb0bqR3cveTmv44td8zdcwPj7Oe++9x6VLl1hcXNzRGrieu/h+s6Nv082bN/n3//7fc/r0af7sz/6M7/me7+H7vu/7+J3f+R0A5ubmAOjt7V31d729ve3fzc3N0dPTs+r3hmHQ2dm56jHrPcfKY2z0mJW/3+pc9ssrb6ccZcTkui7T09O8/PLLvPTSS/64iWiGgeFRLowP0p+Jk02GSYR1PKUoNTw0oQjrGr0d/gb2WNf2+yRcqcjXHO4fSJCOmoQ0geV62J6k3HDJ1Rwu9MXpCiuajocnFSFdAwE1y6Nq+XflxZrFVLGCFikRC/sFDkt1B9eVGDrkaxbvzVeZrcq2ODUcj5Chb1tIG40GV69d5Y033qRaq3H6xChPPvYgJ0ZHCIf90luFwJYGa9dQV2lIdTjpPKUEjjSQCL9aT95rCHtwx1YgBFJpNFSI6zmLyxNFJotNUrEQ0ZCOLgSDmTh92QyxWASvWae6OEPKcLE8xZ18Y9VC2HQkEUPHk2rDBVIphWgNpZM2eXsGVx58ZWurmCAcDlOpVNp7NYf9/d1LxLQWTdMYHh7mE5/4BP39/bzxxhu8+OKL5PP5Lf9WKbVpxLRfI9Z3JHtSSh577DF+5md+BoCHH36Yt956iy9+8Yt8x3d8x55P5rDZrvPDfnPYVXlrff1WOjJcu3aNqSVFeLmCrTsR4nR3jNtL4EjQBNguJCMGAx0RzvcldiRMAr9XqdxwKTRdKpaHQlFqOEgFo50Rvu5MJzfevEU8pBE2NGq2i+VKJguN5XEJ4IgaXXodpwJCKDQUYV0Q0jU86VfNNWyXG7k68VACDY9y0+FENrZpGq/ZbLZHkwsh6OvrY2x0lNA6Bqqu0tul0evhKIGJfmCu5Eop5DoNsy1xMrXVE2kPCk8ZOEqn6XhcWWhg6CZdcZNK0yUVNZmvWFxfrFFuOkilYYVTFHApTuWouoJrlk1fKkIiYlBuOixVLRzP49lrS8TDBsOdUYbSEVam9dQaxwlHKeaseXrDvZjawTsyCCG4cOECruu2R1KcPn160xLz/aSVStzPY+m6zvj4eNtF4vLly2QyGc6cOUNHx/qzsVrz246VJVF/fz8XLlxY9bPz58/z3//7fwegr68PgPn5efr7+9uPmZ+f56GHHmo/ZmFhYdVzuK5LPp9v/31fXx/z8/OrHtP6/1s9ZuXvtzqXRCKBZVk4jnOoc04OK5VnWVa758hxnHWbhTVNoyOsmHf8yCRs6Dw05I+U0Bdq9CRNepMRLg4kuTiQJJsIbehLtx76sr/eewtVIppARA3yNRtPKZSEharNewsNXBeqTd8X79piHSklDVsCDg1RoiL9GwhPSaq2f54hXeB4ENE1EhGD7mSYUsNjpmTTGTc5kQ1xZp1BglJJioUCi4uLVCpV0uk0HR0pQiGTgYFBwG+2XahYTBeb1GyPWDjKQDpyj8nsWvYiTpulUxTgLvvtrYekNUvK3bLPabcoBJan4y0/f6XpUnU8+jrCdHiKQr1MzXKpNl2KdRtX+vsNt5YaRAyNwXQnTrnGYqXGmzenGR/I0nTBVX6UbBiCUsNhacrC81KMrrgB8vcu/H+7ylg2ovWYt+bpCfcQ0g72+9sqPOjs7KS7u5vp6WmuXr3a7oHKZrOHcvyDoGXd1HKR+OpXv0pPTw+nT58mHl/9/WmlMjdK5e3XtsiO4sKPfexjXLlyZdXPrl69yujoKOAXQvT19fHlL3+5/ftyucwLL7zAk08+CcCTTz5JsVjk8uXL7cf85V/+JVJKnnjiifZjnnnmmVVNqF/60pc4e/ZsuwLwySefXHWc1mNax9nOubQW6MOOmg4ylSelZGFhgddff53nn3+eYrHIyZMn+Zqv+Zp1/bQ0TaMvrtMZM5kqNqlaLgrQNBjrjHKqO8HFgQTn+hL0JMM7EqUWmVgIEDRdSa5q03QVhq7RETWoWi4vTJR4bk7w/7u2RLHuYDke08UGpWaDpp6n5tZYqjpUmg46oCQ4rsT2FLrmuwp0xUOEdZ0T2SiPjqR48kSG070ZTP3uJd5oNpicmuS1117jzvQ0HakUDz70YNs7beXd6GS+wSuTJaaLDhVb5/ZSg1emyixW7S1fr6PEvu45+elDfUNRaj+uZdR6AEGTQuBIfVUKU9MEhhB4UpGKhelOxik0HHJVm7rtUWl65KoWhZrDUtWm3HRJdyS4b7iLdFRHL04jmxUGO0Jkk2Fihk4mZhLSdSbyddwVe1FKSRA6jjRWuaN7ymPBWsCWW38ue2Fl8YMQgqGhIT7+8Y/T39/P66+/vm6J+X4f/6CjlFAoxLlz5/jEJz6BYRg899xzvPXWWzQajVXnARunFI8klfeDP/iDPPXUU/zMz/wM3/Zt38aLL77Ir//6r7fLuIUQ/MAP/AA//dM/zenTpxkfH+cnfuInGBgY4Ju/+ZsBP8L6xm/8Rr7zO7+TL37xiziOw/d+7/fy7d/+7QwMDADw9/7e3+Nf/st/yWc/+1l+9Ed/lLfeeotf+qVf4hd+4Rfa5/L93//9fO3Xfi0/93M/x6c//Wl+//d/n5dffnlH59JyGq7VanR2du7pjdwJLWHaz7kq1Wq1PaCw5chw9uzZLW1JNE0jYUqeGsnw9myVxapNrmrRsP074VTUYKZksVBxePJEhtHOnU+NjZo6yYjBfKWB7UlCukZI05DK30e6MlfFrsNZoL/Tj0z+8kaJhlfArQmmik1s10MqkB5oOggUrifpiJhEDI18zcH2JIPpFMOdUQxNoICGK6gVFsnlFtc1UF1J627Pcj1uLtXRtBCdcRPwZ1MtVCxu5mp0xc0tBdpVfr/PXtN6Uuk4CrZbdqeUwMYkzP7d+HhKx5UClisXW9dsOmqQiZvkqja9yTADmRg12+VOvokQGpm4RqUBnvJbEW7n6jwykuZsfweVRpyxjMELV6aZmZpiPp7C1iIoFDFTJ2zqNByP5PKNhef5E37Xe1We8iOn7lA3Ef1gbHjWKxdvpcKGhoa4efMmL7zwAj09PZw5c2bf/eoOsyqwVfgxPj7O9evXefbZZxkeHubkyZNtgVxv3drPIrIdCdNHPvIR/uf//J/8s3/2z/jCF77A+Pg4v/iLv8hnPvOZ9mN+5Ed+hFqtxnd913dRLBb5mq/5Gv70T/901QL5u7/7u3zv934vX//1X4+maXzLt3wLv/zLv9z+fSqV4s///M/53Oc+x6OPPko2m+Xzn//8ql6np556it/7vd/jx3/8x/nn//yfc/r0af7wD/+QixcvbvtcNE3b00ym3dK6wPbaD+C6LvPz88zOzlKtVunu7ubixYuk0+ltC56mabiuS3cyzNcmQhTqDn95JUc8YuBJxY3FOprw+5Feny4zmI6sa+S6HpWmy2S+zkS+wVLVolDziBiCSEgH5ZuzgmKmbBPHH7++WLdJd1g4eg1NE+TrDo4r0TXwPDAMcD1oKjB0Rc2SuF4TTQgMPdT2u6vX6ywuLrK0tEQ4ZDLY07mugWqLleXilaZHsSHIJnxRAn9UuKFBvu7QdCWxbcyA2uue092U1c5QChypoy8L+F7wz0Gs0sWWoOuaxoX+5N0+JAENxz92xPCIh3RcTyGV36Oma4KoqREx/Sq8VDzOUH8/k7kSswslTK1EKtlBsa77Tc6uJKn8FKYlN680lEqyYC/QE+rZd3Fq7atsJAymaXL27FlGR0fbfnVDQ0OcPHlyU7PTnXCQqbyNiMfjPPjgg5TLZa5du8bTTz9NX1/fpudxZO7i3/RN38Q3fdM3bfh7IQRf+MIX+MIXvrDhYzo7O/m93/u9TY/zwAMP8Oyzz276mG/91m/lW7/1W3d9LkKIIxGm1ge7m3TeeoUMAwMD9PT07MqWXwixaqSAVFC2/BRMuekSNXQU/lykiu3y5Hia7sTWX7ZSw+ErN/LMl21Chm/G6kiJY0PDlXeHFHoS21UYOtQ9C88pcnvOodxwcKSibns4nkL4xWCEDA1NKJqOAuUXPSjlF208MtTB3FKZS5U54sJub+TG43E0IdC1jUt9fUcihUTg4VsheUohPX+s/FLNT09pmmA0E+VsXwJ9G+LvKIHBam+9jT6HFq202W6/4lJJKuUaHYkksZDYVUHE3XNYP6pskY6G+MhYmoWyhSsVV4TgtTtQrSo86eJKiev5M7QMXeB4ilzVIh0LMZCJcHOpxlJDMdTXjbSbFIplmlIQSnWQq9ik43Gk2l5/jFKKBXuB7lA3UX3nkf1mzwtbV8S1Io2Wi/kzzzzD+Pj4vtgBHWUfVUdHB48++iiFQoF33nkH27a5desWIyMj94jUkaTyPojE4/FDLxlvfXA7KYBYWcjgui59fX089thjux581qKVVqw0XW4t1Xl3rsrTy3s9fR0hsskIvQkTTYNcxR/8th1hurZYY75sM9YVpVB3iJg6mYiJ5Uk0TaAkVG0XKSFiClzDYqI2T9IzqDuybc/TdD0/avD8m/aqK9t374bmV+WFdajUG7xzswy6QaSng5MnTpKJm+TrLgu5BqYh6E2ESIbXLrV38ZSO7ekko5qfoqrYNB3JQtUmsjzRNxUxuJmrEzF1TmS3l67xq+i2FidYmbrbObZtsbiYa/elKBTDg0OMDPag72BNk+j3jH9voVBoYjniV4qpfJ2pfIOmK3E9jxuLNSK6RhUoNSGkSVypKDVddAFLdYfxbJwL/UkMTaOvw6/Oy9dsqpbEMBOkTQ/qJV6+IulPRYhGoii2l/ZWSrFoLdIV6iJu7I9nYevGbbvCkEgkeOSRRygUCly5coXJyUlOnjzJ8PDwrsXlMPaYtqKVBr9y5Qqzs7Pcvn2bkydPMjQ0tO+i+aEWJiEEiUSCSqVy6MfdTgGElJJcLsfs7Gx7tMTJkyfJZrP7diEIISg3XZ65vsREvsFb02VuLtawPUW16TBTshlMh+mKm6SiJvY2mlU9qZguNEnHDDQhqDsepi7IJkOUGy7JqEm+ZvkLl6Ho7rJouha2NJhbNnj1pD9+3PFYdtXzy85Rdy3lmq5iodykwwQpBC5RErpJwTb46u0iDccjFtYxNT+qSsdMHhhI0pNYvbukUDjKxFEWoCg3HBJhnYklj1tLdaKmjiZ8j76Rrgh1SzJVaDCciawqrtgMVwkUOsYG4qTw02bssB9JoSgVSywsLlAulUmlUoyNjZHJZKjVqty+fZvZuVnOjA+RzXay6V7VmvlNNcvl1lKNfM0hamr0p6JIqWgZpl9fqPLeXJWI6Zf5v3GnylShTmc8hKOU34fmaBjCIWr4AwHjIY1i3eZ2rka56frO7JZHoW5heQodaHhhepIdxMI2r7/2envQ5HbvxBWKJXsJhSJh7O3GDXYuTC0ymQxPPPEEi4uLXLlypV1ivhu3haNI5a1HaxbT448/zvz8/D0uEvvFh1qY4GibbDeKmNYWMgwMDGyrkGE3aJrGZMml4dhYjke+7jKYjrBY9ct9q02H9+YdHh5KMdATxdjGQiyEX7HltG79lT86w9Q0LFeilKTadEFzCSfqoGtonkBJRdORmBqEDQNbCQyhsFuecMpfVhWgIVFoNF3axqUuHpm4yVg2ykLZYqrY5Hxvgv5UBKkUCxWb9+arJKNporq3/FzLDapCIKXiykKN20t1HE/heBLLlYR0gVK+uNUsSTSkUW26zJSbuK5fwZiJmaSjm6dSveXIaa04tfaEPCW2/YW0HZvc4iKLizmUUnR3d6/qvxICUqk0DzzwIAsL87x3Y5KOuTlOjI2uG2UrBO6K4oLpQoMvv7fIXKVJ2NBIhA0m8w1S0uF0t07NdplcqpOMGCQjBrbjUVoeR1KoO77LuO3RlKC0EGcyIc73dbBYtbi6UMORCrFQY7ZUZ6rQIBbS6U+GcZXOYt3hZr7B1zw+zKmuMW7fvk2pVCIajW7bs26lOCWNvc1S260wwV07oJaL+XvvvcetW7c4e/YsXV1d236e4xAxrTyPVs9fT09P25395s2bnDt3blV7zm4JhGmTKbYHydpeprWFDD09PTsuZNgVQrBQdxnqNHhzpoypCxJhk2LDwXIlkbCBtTyjqLcjRFd8630sTQjGu6J85XqeUtNhsWJjORJ9uWhiqeZg6xZGxMKRiorlgoKI7peCS5YbZmsujrzXd1oDJBqtZJPtLu8BCImUfmRVtSWpiEmp6TKwHGIZmuD6Yp2OiMF4NkbCFH71nPA39PNNyWKzTjJsEAvpmLrg3bkq85bHUEZQtnwz2lRUx5OC16cqy+KmiJo6p3vjjHVunt5bK04SDUcJFGLLjWOFolwqs7CwQKlUoqMjycjoCKlUqp1eW4sQgt7ePrLZrD+F9s236c52MjI62u7dk0rDVVr7fS43HZ6+lmOqUKcrEaJuSaYLTSqWS17a9KcixCyPuiPpj5koqbi9VKfUcGi6HlXLbc+3EkiU0jH1CPm6jSYEyYhJw/KwlicF265EFxozFY9oSJAIGzRsX+ii0RTnz5/n+vXrFAoFXn31VUZGR/zRFNuoVMzbeZRSdJjrN4xuBynlnvdONE1jaGiI/v5+JiYmePXVV0mlUpw9e3bDZtaVHLVXX4u1dkSt1zUwMMDk5GT7vdorgTAdccRUKBTuKWRopS4O5Tw0DU35+wX4/8OTfgxiGhohXeBJrZ0SazrbK9joiocoWx4Ts1V0oSjU/f6WmuMSilmEDBvbAyE0pAQDD2d5/8hRfkWf67F8B+8B/t1iK63X+rfAj1g0DVB+gYUQfi2ari1bqEjFnWKTxYpF1fIwdMF02eVcb5Kh1N3elHzdQ8QgYmoUGzZX5qs0HUnNcRElyCbC6AJyNZu+jjDjiWjbMaPccLi2UCcT9VOem9ESp7v/3hzHdVhcXCS3uIiUimw2y8jIyI4qvnTdYHR0jN7ePuambvDqq68yODhAT98Iao0z+myxyWzJQtPg9lKdmu1/FjNlSGgu/R0WA4MCUxftqDJXs0EJ7OX+suXLyT+28HhtukQ2EeZCX3jZf9ElbupogCM1IrqB7UoSYcgmQuQqNrmqTaHukI4ahMNhMpkMqXSKyYlJZmdmGR0dJZXa2ky44BSQSNJmetvv10r201lc13VOnDjRLjH/6le/uq2R6McplbfeeWiaxsjIyL4dJxCmI4iYms0mjuPw3nvvoZTat0KG3aDrOj1RxVLNwZH+3ok/GhviIQ1Ng7Cuca4nQWbZbmZkG71Mt5bqdEYNuoaSFOou2YTLpVt1lFYBTaAj0KTClS1DUo2QsSx6Cmq2XNGzsoEvFy0h9f/tCr+3KRLSiRmCO0WX0z1xCnU/ahNAdzLCQCpOsenxzlyVdDRDIuQvoa7yN7Am83XuFJpcz/kOFEr6fm6Fmk3Y1NAQdESMtigBdERNZopNCg1nS2FSStCUOrpgw1JyhaJSLrO4mKNQKJBMJhkaHiadTm8YHW2HSCTC2OkLNCtFrt+eZHL2NUZGRlcNx5urWMxXfCGXUmEaGqmIQdORVGzFRNHho1LSnQgzXWr4n5flUrcdbFfd02vkLX+ebsmi6UgSIYnCLyEvW1C2JA3XH4vjSL9qz1WCRLhG3fYY7YyRFR6mptGd7aars4vZ2VmuXLlCMplkbGxs0wnKACWnhFKKTCiz6ePW4yBGXrSaWVeWmLd6hdZzoTkuEdNhpRQDYTqkiGltIYOu6+07paO84DRNIxtW3GzY3Ck2QUHTlXie8osHHMlwOsJ8xWa+YnNqHYuftTQdj+lik6rtUWr4rtHTtRIVUfatiISGJiCkC9xlcRJ+OypKOYC+rfbQ5WI9AFp1JOWmS65sI4QgHTNwpWJiqU7DkcTDIbqTUQxdpyuu+WXgdZuwGUEhSId1rldtZktNqpZH3fKQy1Y4ugudMZOYqS/PjvI/M8vz8DwIGX5iaW02znIlFctFAKmogS50nOW0mVTcU0ruuA5LuSUWFhfwXI9sd5aLFy/u6/6iUhpaPMuF+zIsLS0yOTnB7OwsY+NjRKJx3pousVi12i7g0pUs1Wwipj+u3ZWwWHG40J9EKsW1hZqfrt2kMMZbvq7mKxZLKEK6RNNNLFfiAtLxNxCdmo1UEDE0POlPLJ4uNRmKuDw+6EeImqYxODhIT28Pd6bu8Prrr9PT08Pw8PCmLRNlt4xC0RnaWTP9QYpCa9hqq8T86aef5sSJE4yOjq7Kmnied6i2aRvhuu6m73FQLr5PxONxcrncgT3/ykIGwzDajgxXrlwhkUgc+V2QpmkULb/oYCgdpb8jzFShyUK5iQKiho4mBHeKdWqWx3M3DS70+555GyGEYKlmM11s0p00cY0GzVoNbzm943oglcKVCm85YtLx70qFMvHUOhtLm9D6GmiA4yos1+PxsTSxsE6x7vDVWy4RM8xAOoKha1Qt1492FO3je0onHRJUiy6zJZum69FwvLZA2q7Ek34hwGhXDKkkV+cqzFVtbFdi6IJszCQZyeAqRa5qc32hxnSpicAf7ZCKRDjVm6QzfvczdxWwbF80OTVJpVwhHo8zODBIpjOzp+hoPaTScKQ/vNFRGtnuHjq7OpmZnuHdd96hLBIslv2BjbXlz0gXfsRoaBpdUQ1D990x4mGDx8YyDGWiTOVrLFZtNME9zuvtYwNCQVPqVB2DkO6h+UbyGJrAVQpHgilAoig3PU50h2nYHtfzdU5kDE6ueD7TMH3rsf4+JicmeeWVVxgYHGCgf2DDu/qKW0Ei6TK7tr2AHsaQwGQyyaOPPko+n19VYt4qxT5OqbzNbpL2az/8Qy9MHR0d3L59e1+f03EcFhYWmJmZoVarrVvIcFxmMmmaRtnyKDddXE9Sczx/uqymYTuS+YpNqekQMjRMTeMrNwpICX/v8SHGN3AZb42ZaEgH22hScx08BYYucB0/3Sbwv/Bq2a7R0DSipt/QWbMc2IGlji9svisEQuBIRToWQtegpyeCLQ3enqkwX7GpND085R8/GTFIhFt7VwJbast7IxLbk2j4i6aHLyANx2tHEcW6y3vzVXTN36ezXUnd8rhTaDBdbPLefJWpQgOBIGxoZOMxHOnQnCnz+GiaSEjHdV2WlpZYXFjEkQLDMLhw3wWikf1rDl35LrnSr7prrR1CCGwPQrrB8PAwPb09/NGL16hWKqSjYRxPQ7kSXQiiIY1oSCMW8gsV0ssDJHUhGExHeXQ0zbtz1W3cT2j+fwJsqWPgoQv/RsUQAg+FaQgMXafY8FOwfR0R7riSQnP9Z49Gopw9e5ZKpcLt27eZn5tnZGSE7p7udQskqm4Dx8vTF+nc1kJ6mNNrOzs7+ehHP8rCwsIqk9itxpkfFkEq75CIx+PU69sfFb4RLUeGmZkZFhcXSSQSmxYyHJcptpqm+aPKHUmh7iJQVCwPz1PtCEfgOy+AwlOKN2YqpN9a4G892MtQev1FNJmQhKoNJkoO5aZLsWahpGxvigsBpu775Zm6fyftSP8OXQkN11UY+vbCJh3/OSKGQdNxef5Gnol8g7BhMJ5Ncr4vQdX2mCs1SUdNBP7rNXVJzfZIx3ynB8uTWNLEk8of8S79QYY6y3f7QmHqOoWajfQk2USIsKGhAbGwQanhcOlmgf60n3IK6X5hx0JFMluucKY7RtORTCyWCFkl8vk88Xicvv4+bt++TW/fMNHI/o9wUAjcDZwk7ooThENhhocGeKswQ1Q1aQgPoRtomuYXNPh/QWfMT2dOFxukoyZ12yMeMuiIGDQdr733t+ocFLhSpxXftp7LkTpofpWLJvx9J6l8wYuH/LL0YsPG0Pwbm81IJpNcvP8i+aU8ExMTzMzMMDo2SiZ9d19JKg1XChzRZLaZpy+ydVS6mR3RQeBXUva2XczfffddPM/bch/tMNhqSGAQMe0Tey1+aDabbUcGz/O2XchwnCKmtClJhDUmlxxcJbGd5b2V5ce4HoRNsKUivtysmq/ZvDdXZSAVWWVo6inJvFUkFrexHBfbsrDqlu9ppzRMHeJhA0Pz3cZ1AZ6naHoSx5LtYgiFhudJ9G2IU8T0S5Mbjl89Vqw76JqJFJKpwhKzpSaJkM7Z3jh1y8PQdcZjJlJJ7hSbDKZ8Z/GQ5kc3UoXQcNr7S+CLny78ER6OJylaLhd6k+grFksh8NOXiRAN2yNX9VBCJ2xqVBoO1+fLCM/GrCgeHO3iwoULRGP+YjNxewJX0R5Zvl/4qbvVE3rX4ouTIKRJxrtiZJNRGk6YsZjLbL5MoQkCnRPZJJ2ihuMp3p6pAIpi3aZm+754XfEQCxXrHlGSSuDKVvx5z9FxPB10P20qPYXwQBMuTdd3n3c9ScqArtjWy5VA0NXV1R48ev3adeLxOKOjo0RiHat8/2pek5lmnoFI56bidJgR00paA/0GBgb4yle+wtTUFLVajbNnz94zJeCwCCKmQ6Kjo2PHwtQqZJiZmaFQKNDZ2cmpU6d25MhwXCKmiuVxqywJGQJHSuq2xFN+ekohlx0JfBdw0/BTVk1H0nAk+ZpDw/b3GgCans2sVaBcrTA3P0++UKFoC2ou2NKPjoRgeZyB5u8reJKqvbzJvubcPDSQEl3bXJyay428Hn4RhKkbND1FxPAn6F6dr3GyJ86ZnjgF3aFpS5qOi2noNGyPuu0yWbS4lXexbM+3TVLaskebPyxR1yBs6nREDGzXT0A6noeu3/0KOa7yDW81Qd2GQt0jpLuUPQ/bdsjGdJQRYmhsgOHh9Lp7MX5L1t7FSSnwlIanxLbmMwnhf0ZdiSifONXFV24sUWxoxBMpYhGLDE0GI3XezrmEQy7DEZd83ebNmQq2K5ejJUnU1KjYdz9J19OWG6A3VUYcT8fQ/D0nBFiuotTwi1hMXaM3qZEMb39BbI0R7+7u5s7UNK+89g5d3d0MDw+vKrNveBbTjSUGol3oG4jTUQlTC13XCYVCnDx5kmq1yqVLl+jr6+PUqVP77mK+FZulFI/MXfyDyE688qrVKjMzM8zPz7cLGc6fP78rB2Fd17Htg50hsxW3l+r8f1+Y4fVZgRlvYi2PNk9GfPsXx5OUGi5yeXGOGhqaJoibOlXboWq5bSeIxUaJa3O3WVxcpNFoUHUShCJxSjV/jLbvUA629JtfO8J+m2zFkpvuS3hqa3FqLeGeFHhKULUVdddv5gzpAkMXZKoG70lJpelhudJ3HgAeGEzyzlyVazmLcl1iawqh+a7lntTQkMBdE1lTF3TGfReL+YpDb1IQMjQajkel6TLelcR2BbOFOpWmBUohhIaLjuaG6ImGKDRcnr9ZwPEkXfEQA6kwZRvmShZpaZCOGiB0dG134qSWrYW0HdobCeH3FF0c7GQwE2MyX8eWkr6OCJW6xZ++PkGp7tAlBO/OVbhdqPtjSDQoNvwmam850vbdLLT2HuJ2Du4qHQOJofl7TgAxQ6M/FUZ5dYrNnd/I6XqIgZETdPYOMjExwWuvvkb/QD+Dg4PtBbYpbaYbOQajXeji3kX3qIUJ7lbltUrMr127tmWJ+UGdR5DKOwSSySS1Wm1D92LHcdqODBsVMuyGo07luVLxx2/O8/ZsjaIF0m1SbUocoOE4mLrv4GBorNoXiod0htMRHAlhXVCvlnhx+jrTuTmi0SjZ7m66Oju59eYitwrzeFL53neodkm3VFBsbuz0vZYtxUkpXKm3rYkkfuTkz2zyy5Bv5euQ922HxLL5qxDw7lyVhiPJxgxyJUUyZnKhN8lbM2VAx3IFIaFIxwSRkIEmNM50JxjpjPDiRJH5igPLYx0GOkIMhhu8OFFhuuQXwEtdw3YVuiaoWw5zUvLmnQr3DSRBwOXJIl+uO9gVWApVSMZsBlMRzvUliHCvOHnLFX/V5RL0rkSI1Ip9KYXAUb4rxm6WUj9yEmRiETrj/mJXt12uzFVJp9I0LRfX87i9VKHu+hOKteXqypZLh1yzn7SDo9P0NDwlCRuC7kSYs31Jmo5HvqAoNnfwfVlOi3r4qbtIJNIukJiYmGB+ft4v+OjpQdM0LOlwp5FjMJLFWNNwfByEaWVVXjQa5YEHHljXxfyg02xBKu+QWC9iUkq1HRm2U8iwG446lTdfbvLqdJnFqkXVAU3ebWiVgOXB3S1qiAhBKhqityNEPKxjNxuUFm7xF1aVTFeG8+fPE1sew9x0XG7lfCNYgX/3u8MK8HvwlACPe/aclARX3TueoXX2yzUb5Gr+oqbjDxrUhSAdNVio2MTDBqm077tnSMlS3UFvOZcbOo7nETY19OVprU1HMplvciIb50w3lMpl3HodzS2zUEsQSaToxmWxYlNvuhjCjyoaDr7jQdiitxaiZrlMFy1KDRfDg17bI50Q3FqqEzIEp7oTmPgpLgDHk7w9W2G62PTTjPhR7JneOKOZKBJjORW4N6RSLFQdPM+l7jhMLNW5tVijK2Fy1QZPGNjSRS6PBVn5fnvSdwrZ/Xx3geNpCDxSUYOoqWHqGjOOXL4mt6ZV/i/XuSaSyST33Xcf+bxfIDE76ztIZDIZbOlyp7HIYDSLqd39nh8HYVpPEDo6OnjsscdYWlri6tWrTE5OcurUKQYHBw/sfDdL5e1XDxMEwrRqj6ler7ejo50UMuyGo46Yqk2PhYrfia/hNz9utqbZrqJu2RSLFqrqEIlLekZT3D92Am3NhfrGdJXFqoVAYe2b9go/ZbdCnDxveYT5Dr4LHv4UXIVvkySWo7m0EcZ2JYsVG5T/JXOkQheCSMgkHQuRq9SJmpJM3KRpWdy4k0fYNc50RRgY62XJi1DJNRiKgUeDQs1/fn+LRUPofuPyQsXmjTuVZdskQXciRLnSpNJ0mS42qDY93p6pMNQZ4XRPgkcGkyTCMFNqMlnwiytCyynU0rIVUioaJbYPM+mKdb+oZbrU5NpclaVaHctxqTseUcOPXKMhP6XbUsfWR+xKDbnDz2NdhMD2dHJVl1jIomq5VB255dRg8F01/BuVzZ7eL5DIZDIsLCxw/frdAolEIuFHTtEsoWVxOi7CtNE5dHV18dGPfpT5+flVJeY9PT376rOplEJKueHNebDHtI+EQiEcx+Hrv/7r6e3t5cd+7Mc4ffo0XV1dB3oxbuYufhgkIjpS+kP7lAfOJo9VgK1gtuxSMhXpjOBUIoY0Y0jEqpTRYtXi+mIVbzm9s7+0xEmhWN5U38X3TgEufrWhIRSVhsO7CwqkQgl/9HvD9gdAaUJgSEWh7iIx0HGZvDON5tmkYklqkV66R3roSUd473qeeFjHEH73TMPx0IR/vKbj4UkwNLA9SbnpEjE0GkoSNjTfnkiDN6crfmOvUuQbNlfna8wWm/y/7+9hdrlZd6lqU266GLogFQlRthW5msNIeG9f56YjeWO6TKFmk69azJWb5OuOXx2pedRtfwbJkOm/L63Vv1UKrvYUE69BCCYL/h6soflNvsWGx2ypSX9q/QbPVin4dq8JTdPo6/MNbqenp3n7rbfJdGYYHR3lDosMRrKEdfNY2AFt1WC70u37zp07vP3229y8eZOzZ8/S2bkzp4uNaK1Xh5HK2/O7/a/+1b9CCMEP/MAPtH/WbDb53Oc+R1dXF4lEgm/5lm9hfn5+1d9NTk7y6U9/mlgsRk9PDz/8wz+M667ed/irv/orHnnkEcLhMKdOneK3f/u37zn+r/3arzE2NkYkEuGJJ57gxRdfXPX7jc7l9ddf5/u+7/t49NFHAXjkkUf4V//qX/Hggw/S3d194BfiUafy0lGTZEjDleBuehncFU+peegJC0+4JMMmk0WHhbK16tEzxSamriEk+5JWWotSAssz8OT+3QnqQlCxFcWmHwTMl5u+K4Xn7+lYjsdCuQm2hdV0CUXiDI+eort3gHAojLWswPryAMR4WCcV80fTu9Lv/QKBpvkpUsdVuJ5Hw/Uo1l3myxa6gPmyw8JyE7DlSsoNl6W6w1dvF3l3vkbFEtwpNpgsNKk7fjn6lcUGuYpzjxXSbshVLfI1G0MX3F5qUGzYvg+hpqNrhj/+A1isO0RM31bKkX5FnVq1q7U/H7zjQt0B0OlPCCRwfbGGu6ac0U8hGrhqdylEwzAYHR3loYcfQgjBq6++ys3bt5ioztH07COPmFqRynYEoWWm+olPfIKenh4uX77M5cuX92XmXGt9PoxU3p7e7Zdeeon/8B/+Aw888MCqn//gD/4g/+f//B/+4A/+gKeffpqZmRn+9t/+2+3fe57Hpz/9aWzb5vnnn+d3fud3+O3f/m0+//nPtx9z69YtPv3pT/N1X/d1vPbaa/zAD/wA//gf/2P+7M/+rP2Y//pf/ys/9EM/xL/4F/+CV155hQcffJBPfepTLCwsbHouf/2v/3WeeuopKpUK/+N//A8Avvd7v5fR0dG9vB074qhTeQp/AdVg3f2ZuyxfhIaDiPiD9CSKO4UGrqtYrK5+DdWmR9TUKO2guGG7yNb+BX4KT+2HrguIhnRMQ+Dij8wIGRqdcZNEWCMiFEgPhUILmXR1dZJIdIPmRwiKZacLAf2pMPXlXqp01CQRNnyfPcTy6Hb/+YXmG8Zarv8MTVdSbMLtfANXKkxdEDMNv+JRQaFu8+5cBVdBrqZIRXQiZphkJIwuNH9syD6sB3XLY6bQ5I07FaaLDSpNSdNRWI6k6YBavhnwPJBSYbnacip17cH3Z3HygELdZbbicnVJMVloMl2oU7PuXlut5uH9+CaFw2FOnz7N/fffT7Va5aXLL/PSjTeou80jFabWOrGTczAMg5MnT/K1X/u1xGIxLl26xJtvvkmj0djTeWiatu55KKWORyqvWq3ymc98ht/4jd/gp3/6p9s/L5VK/Kf/9J/4vd/7Pf7aX/trAPzWb/0W58+f56tf/Sof/ehH+fM//3Peeecd/uIv/oLe3l4eeughfuqnfoof/dEf5Sd/8icJhUJ88YtfZHx8nJ/7uZ8D4Pz583zlK1/hF37hF/jUpz4FwM///M/znd/5nfzDf/gPAfjiF7/IH//xH/Obv/mb/NiP/dim5/KXf/mXfN3XfR1SynZl3mFy1BHTZL5BuekRNnybIJ+74yXuoiBsI3R/MXA8SGgahYZDsengKlBSQ2j+azF1wZW5Ks1tTLrdPgrP0+4RUE9p6Erufp8d3ytPEwLX83A9fxZRrelXvNmeLyIhQ0cgWKpDjw26IahbUG5aZOImXcvVa8OZKMWGw2yxyWLNIWxoy+4P/hgIb7nR1dQEsZCBtiywYV2j1vAFTdcgGdbRNX8UouVKXE9RrDtk4iHS0RCzFQibjj/tVkAyou+LFBQaNjOlZnv8SfuqUMtipDSQ4GiSQk36fWYHjJSSsK7TsDSmCh7C8Pfulmo2lgPRcJjuZAhzC1eInRCPx7lw4QLFYpGJiQlsy+ZEemDDyt2DprVO7CaFFgqFOH/+fLvE/Nlnn2V0dJTx8fEdl5gfpi3Srq+sz33uc3z605/mk5/85KqfX758GcdxVv383LlzjIyMcOnSJQAuXbrE/fffT29vb/sxn/rUpyiXy7z99tvtx6x97k996lPt57Btm8uXL696jKZpfPKTn2w/ZrNzee211wA//IzH44c++uKoI6ZXJ/LULWu5qqp1HmsuOs1DRJttUQJ/nHnN8qhZHtOFJoYm8BRI2ZprBBXL3bfdBqXA9davugPwlv3t9kLLXSCiSwzPWh4x7guQoQkcT9FwIBIyCGsaxZpDxXLJJmJcHOggYvqv3dQFDwx08Nhomov9Sfo6wmSiJt0Jk1TUIGIKQoYfOnnLkVE8ZBALa3RHIGKCrvtFF81l77265eFKRTpmEtUN+jtijHXF6QiF6YwZjHdFySZC7SGMu0UpRbnpIATUXQ+1TvevI8FWAsc1cdROl47d3ag0XSg2XJqeoGgr5oo2L97K8+pUlbfm6rw8UeC1qRKWs7/fJSEEmUyGBx54gGgsyo3CNE9/9SsUCoV9Pc522E3EtJZYLMaDDz7IRz/6USqVCs888ww3b97c0Rq0nR6mI63K+/3f/31eeeUVXnrppXt+Nzc3RygUIp1Or/p5b28vc3Nz7cesFKXW71u/2+wx5XKZRqNBoVDA87x1H/Pee+9t+1xgZ022+8VRFD9IKVlcXGRmZobL7xYRUl/OuqxzF2Q4iJDD2v0Chd/XEjF1HE9xM1fnVHecsKEhpIbjKcLG3sXCP1+B3EaTqCc1dG13kZP/eiTxCMTCGrF4DLtsU2q4yx5pCunp6LogEzNB0zjXnyQbN0lEDHQh/Jp130wQQxf0doT9WUWFBnMli3jYJBPXCFVtarZL0/FwPUk0FvL9AT2/UtDQBdLz06ES5Re9STAMheMIMvEw8xWXbMKgJxlGoCg1miTDhn9ue0Ap322hI+JbLnnKLzhYUQ3up1KV7y7u7z3tpNxh5f7T9j8ohX8z5JvpKmaqDgtVycNjvuOB60mmiw06YyYnew6mejYSiZBKpZDAV16+xHD3AGfOnDk014VWCm0/Fv2VJeZXrlxhYmKC06dPMzAwsKXwHeZ49x0L09TUFN///d/Pl770pX2dEXNUCCGOZFhgK5V3GOmBWq3GzMxMe/RGZ08fXX0RLhfyqHuy8wrCFkLfWDQdCZoraTgur06VSEcNnhzPgK5RrHvk6/aGow+2h8KT+o7EbXfidDd1aYZN4rpDyNT9/hy1LIxSQwkw0EiaGpWmC0rRsTwMUK04dkucwK+we3C4g6lik3LTpeF4GIZAczUQst2H1Kraq3mQChtUbEmp4a1Y8BUhLcQbs1W6EmESEZ35iu0LIpAI65ztjRELbX/BKDedZc9AjXTUQCmYr1jULJdiw399miYIm9Cw/X0wT2oIBLqAsCmoWr5obmUXdS+7u9YV4LngeII7JZezlsSVnj9h2PZ4ebJI1XIJGTrZRIhsIrRv36tW4cHg4CBWby/VO4VDdV04iJEXXV1dPPnkk8zNzXHt2rV2iXl3d/eG79thpvJ2LEyXL19mYWGBRx55pP0zz/N45pln+NVf/VX+7M/+DNu2KRaLqyKV+fl5+vr6AOjr67uneq5VtbfyMWsr+ebn5+no6CAajaLrOrqur/uYlc+x1bnA0Uyxbd2dHNScFc/z2qM3KpUK3d3dnLtwH3NNg7cXa0yXqtQdj1XN9JqHCNsgtk676JrA1DRsT3JrqcFYV4zOWIjb+SYLZW+XiRug7Rqwc3yBUAix3cXSP46mCYoNF0cHw10ekKcEuqYRMXU0/NL3QlPSGVvu4Vl9yuuKUzYRYjAdgWLDL7UGEmEN0zDRUMvl5IJ42KCpwWgmyjuL1buJVQUR03cwny1bPH09zyMjKTQB2YTJQDpCPKSjpD8OPRMPtdOK6+F6kqvzVSYLDSxHoglIxUxQkK87/r6a6zFfsagvW0X5e2P+/p4AwhokQtpyVCdQHtt2gd8tAnClwFWCiOHP+nr5dtkXTsdhKt/A9iS3c3V6O8J0xkOc70tyqie+L+K00l3cMGJ0jEUZHB5m/uYkzzzzDCdPnmRkZOTAFu2DilRafoK9vb1MTU3x1ltvEYvFOHv2LJlM5p7Hb5XKaz3nfrDjpOXXf/3X8+abb/Laa6+1/3vsscf4zGc+0/63aZp8+ctfbv9Na/DVk08+CcCTTz7Jm2++uap67ktf+hIdHR1cuHCh/ZiVz9F6TOs5QqEQjz766KrHSCn58pe/3H7Mo48+uuW5wNGl8lrnvJ9UKhWuXLnCc889x+TkJD09PXzsYx/jvvvuY9E2eWWqhOVKuhMhIuaKi71VdbcNUQK/F6dmuwj8fZi5ssXtpTpThQaOp5Dezi9QJVl2od49nhSoddN/60eA6bBGR8SvTizbULE9mo6OLjRMXdytWhQC23XJxM11o5OWOLHi2LbrFy/kaw6OJ4kYGnVbEjF0HhxM0RExiIU0+lMhEqag0HBo2qDhzyYyTRMPaDj+eHfb8+iKm8RDBuWmS7nh8uZMhRcmirwwUeH5m3mmi80N35s7xSZXF2pEDI3+dJhsMsytXJ1XpopkEyFSsRB9qQipiOmLkvQFobW/p/D7sEzNaL+bCoG7i8/63ndv49850jeB1YW/8JUaNneKDYTQydd8E96oqVF3XEoNl0LD4fpilXJjfypDpZS+36Gn0WpDr+ge4/ef56GHHmJmZoZnn32WmZmZfa1Ma3HQfVSapjE6OsonPvEJstksL7/8Mq+88so9N+vHOmJKJpNcvHhx1c/i8ThdXV3tn3/2s5/lh37oh+js7KSjo4N/+k//KU8++SQf/ehHAfiGb/gGLly4wD/4B/+An/3Zn2Vubo4f//Ef53Of+1zbEPW7v/u7+dVf/VV+5Ed+hH/0j/4Rf/mXf8l/+2//jT/+4z9uH/eHfuiH+I7v+A4ee+wxHn/8cX7xF3+RWq3WrtJLpVJbnkvrNe1Hnf9OaF1onudtOqp4O7iuy/z8fHswYW9vLw8++CAdHR3tOxjblVxbrBEP+8PxQoa/5G4ndbfuMSWUmi69ybBfeaYUM+UmdctD0wTC81Nhmra9IenrVd3tFk8KdKFYbRZ97xcqsjxYsGVcW645GMIgFlLYrsR2AcPfM4sZGvGwwVhnjM4N9nPWRk5TxQaJsM5wZ4TJpSYRU6O3Q1CsuxQaLrquoSmFuXwtlG2PkKlRsxW6phNebvR1UctNuL4tUjpmcGOxynzZZjAdobfD/86U6w5vz1bRPBvZrNDV1dUejyClX+IfMbW2G7yh+ZFv05E0XY9c1SJi6MRDGt4G+3s1F9zq6t41v2Tbb4TdHa3j+K7zq95PT28VHy5HcJKaBQKbqNlgseIQD4fp7TBpuhJDh7rlUtQFhYbtR4R7RHq+xdHaVzffLNOdSPLUU08xMzPDlStXuH37NufOndu3plY4uKzKWgzD4NSpUwwPD3Pjxg2ef/55BgYGOHXqFJFIZNOIab8F+UCcH37hF34BTdP4lm/5FizL4lOf+hT/7t/9u/bvdV3nj/7oj/ie7/kennzySeLxON/xHd/BF77whfZjxsfH+eM//mN+8Ad/kF/6pV9iaGiI//gf/2O7VBzg7/ydv8Pi4iKf//znmZub46GHHuJP//RPVxVEbHUu4KfyDjtiEkLsqTJPKUW5XGZmZoaFhQVisdimfn4Nx6NhS1JRf5hbue5QthxEdHupu/Wo25JK06HuePQmwxRrDlXbHzIo8dNASIG22YK1h9Tdxki/lFxKNpsB5ynRHj6npL/wZxMhFqoOEUMjpEsM3U9XApztTfDQUEfbUX09WuKkaS6luovrKUp1F8uVKHzX8prtT7r1pELXxXJZOdQlGMLAb19SOJ5cLoLw50L1JkOEjGVHbFdSd2R7kqyUEk02uXWngLXY4PxAmrfffodstovh4RF0w8ByvbaVUQtjeZPLWR5nYrmShYpEKuF7/Al/T7H12hT4gr32dSuBKwXGtm5ENuLuuUnFqtlJEjAE7fSi7XrMly3iYZ1E2EQTOigbQxPYnt97tVf83hzdH3OyQcSyaFVQKAYHB+nr8wc+Xr58ma6uLs6cObMvdmaHWXQAfj/XhQsX2iXmzzzzDKOjo9tyn9gvhDqI2PN9xuc+9znAd7E4TJ599lkeeuihHQ39chyHubk5ZmZmaDab9PX1MTAwsOVz2K7k/76zQL7mMFducqtY4qszOfbapd8RNjjXl+DbHuljutTkN56boul6eN7dZ9ZQaOvsQ7T2Lw4KHWCTgoiQDiPpKBXLN2bFcznRm8L2JEtVh6brEY8YGAj6UmE+85FBuhLb2+gWwHM3Fnhtuoypa5Tqft9Xqy+pK+6b4ZqaIBbWWVwoMO+E0IRGtelieX7DoqsUKMFgOsT/cyZLNhkGBZcnSyRCOqeyEUqlEuVyCV3TccwE949keWi0g1Ld4trNCaqVMmfGBpn3YsyVLfo67hYt3Sk0uDJX5ZHRNAtli7dnasxVmixVXTQNTE3DceWqRGgreln/dSsMXbKXJls/WuOext2oDiFTx3ElsZABSiERhE1/tpehwVg2jONKxrJxvvFC764jJqX8vi2p4I033mBoaGjTKCgTitEfTQFgWRY3btzgzp07DA0NcfLkyV2Nxmlx584dZmZmePzxx3f9HHuhVCpx9epVCoUCqVSKxx577B6B8tOdYt8K4j70XnngR0xriygOg+1GTGvHtieTSUZGRujp6dn2nVTI0DjdHef3p6bJWRVCUX/O0F7QgVhIw5WS64t1OuMmsZBG0/FWPbNE+KOzV0ROnif2KXW3Ov2z9jetiG09cbJdwULVxfH8/aOQgHLTJhEx6ekIEw8J+joidEQMLM+fKbVdFBA2wzQdSTJsIOIGuZqNlP4IjERY55GRFCFdo9SQdNpFwm6U6ZJFNKyju35xBK4iGdHoiJjczDWYLjYJmzopU1ItV7hVbZJIxOnr7yccjjBftklETd6dazBbqtEgjROO8Ny1BVKmwo10MltSxMIG8yXfD0/X4PpCDaUEVdvDEDqm7uEphe3da+67+Y6QwPW03YmTUnhqfQ9EgUSiETI0YiHf59H2FE3HxZEanlSEdLBmJZ0JneFMdEei5HqSubLFUtVCSkE6HqUvFfZHvS/vMW1Gwa6jlKI/mmpHHCMjI+2xFCdOnNj1WIrDSuVtRCqV4iMf+QgvvfQS1WqVZ599tl1ivjJK2s+IKRAm/D2mGzduHPpxt3J/sG2b2dlZZmZmcF13z27nfWkTI2JhKkXN3nsPlYfvRh0yNK4s1Lg4kCQe0qk3HaprXpZUy+Ik1J4LHFaz+XMpBN5yWfPK742Uwq+8ExpmyB8dLjyPuq2wXJt01ORMT4pIyCBfs3E8tWPvv3TUoDMWQeHvV0VMjc54iJihkU2G6IiEaNqgcMhGoTud8H3yPEVIlyQjOh1hHU9BKmagC0WhXEM5FqdT0NGZwtYyJOIRXBSFskVvMozjKd6br5GOm/SnBK4MsxAKo9wGsfoilUaYORmn4ih6kmG6YlHmqxZKCU51xyk1HRRqeUikZGXvqs5GZSSr3/OdilNr4u5mNyueBMeRxGMmnuZHZ03HFxUNgeMCIejviOF60jef3STt2sL1JG/PVLidrwG63yawZDGciXD/UAol1T2VmOtRdBpIFIPRdLsN5ZFHHiGfz7eLrs6cOXPPgr4Vh53K2wjTNP0R9ZEI165d49atW+0S8/0mECY4EksiWL/JVilFPp9nZmaGXC5HOp3mxIkTezaWzTXrzDWq9HVEiId1Ko7Da1Ml7D2m4pseTBWa1G1Jd8JcbrzUENx7p+1Jgcf2Rn2vz86bM31WiBMKV+mgIKKDaWhYjkdv0gTHI5kIYRoaQiluL/nedeWmS1c8xJvTZU5mYyQi/temI2JgbrLwJSMm3ckIyZCGpxyipoZSyheaSAjPE5SaNsmIQbgBuqnz4HCKpiuZL1tIpSjVHRzPQ7NdUlqT3o4IWqSLzo4EDwx1MFOymC9bgOBMT4Lhzghv3CkTMjTiYRNPgal59HZEyFUFD5zsZ2ZmmplrOUazHfR3dSF0g1Q8xEyp6U/TbbqEdY3r8xXKlj9ssZ2W1diWa/xOxEkq4ZvybvAwsfyfUlCzPBzPw5ci3yS3dVkoqVis2LwuKxQbDn0dEc70bZ0mX6zaTCzVycSiGMt7eI7ncafYpC8VQSqJtkXE1KLsNJGqwHAs0xafzs5OPvrRjzI7O9seS3H27Fmy2ey2nvM4uJu3zsMwDAYGBujr62Nqaoo333yTRCLRnsiwXwTCBEdiSQSrU3nNZpPZ2VlmZ2eRUtLf388TTzyx5+5yV0pm6hUqjo0QgsF0hDdnbBKGSSysYzf2HjkpYKnmu2Kf7onzyqTLWgsaJVeMSdDYQa/RSnamaBr+NoXvXnC3rLkljGHDWLYG8vuVTAU9HSHSUZPri3VuLdUZzkQ50xtnIBVmptjkj9+q0pMMEQ0ZJCMGZ3vi7aq4tXTFTYbSESbyDWKmQWfM9IcA6iagMV+xMHWNE9k4c0UwdY26bVOzPMK6wLJsarUaNQdMZXLiRD9dqRiu64/N0ITgfF+C0z0xv/lVE7hS0nT9URrQGpqnYQiJlOAJQVfvIH21MF69zPUbN8l2d5NOpwnpGjXboysR5lauhmnoGK4irPzCDdv1qzG3S8tg1R90uN5n50fPapPxJa3a0ZVDLD23ZSV89zHacqu4UFCs2TQdl//PCzP8jfu6uDCYIhXdOK23VLVwpdYWJQBT1wHfk6819Xi7VF2LyXqe4Vhne4aUEKJdnDQ5Oclrr71GOp3m7NmzW+4PH5eIyXXddmFVq8R8cHCQW7du8corr/Dxj39835qNA2Fi9bDAw0TTNEqlEvPz8+TzeTo7O/d1FlTddbhTK+OsSBcOZSJULJeJfGN/3LmXUfgb8o8Md7Cyx1MpfCVatemk/BLgTV/izqKjtZiav9ArpWi6ajl1BwiBQhLWIRHRSEdNbFeiawJbKlIRk5GMXyQQNsOMZ2NULZdLN4vMV6zlMnLJQDpCzXIpNxw+fjJDKnbvF1LXBONdURxPsVCx6AhH+NiJGKBhS0lH2GAgHaYrHmZOCLoSBtVJm7l8jbiwcNFoKB0MQdXTeW+xSZ+lyMRMTF1rG5caK64VXQg6IiYLFZuO5XsaiaBuKwxdI27qVDyF0EMMDA1Rr9VZmJ9nYq5AQUaJRkNULY+5kkXN9oiaOobuR8AgsZfzmdu9rWh5HRr6anHaTurOP/d7EWt+LmGV00jLdHa+bPGld/NUbcn9gx30rTfHSWkoZWw4LsOP1HY+9qLm2kzW8gzHM+grLnRd1xkfH2dwcJAbN25w6dKlVSXZ63HUYzdarCeQhmFw+vRpRkZGiEaj+3asQJi422B7WO7BjUaDmZkZSqUSlUqF4eFhzp49u68WT7lmnYVG7Z4FxNA1Lg4kiZgaz141KTTk5uXcO6Bmu9zON2i6El34s3rWt4DwRUIt+63dZaUY7f5zEEBHVMfUdMqWg678ZJDEv6PW0AgZvgdb05VUbQ/bU6RQREI6N3I16rYkEdaYLjTJNxxyFYtS08WTivfmq9xcqpONh4iGdEK64K+dzd5TRj6Zb3B9sebv5y1bHPUn4wx1hle9PCUlSkkKc3dwyk1MPURDS5CvuzRd138vdb9Kb6Fis1Rz+LozXasbpFuvXQhGOiMUGy4LZYtE2Pe+q1guJ7ti/qgMTdIRDTFXtjB1E9XRx/R0jkajzPlQlIQRptBwsF1FPKzhWC62d3c3T1vjobcVClal9aRiOXW3u8/43kvqbgFMy5I4EtLJxEM4EqoWvDdboTNutsvtwW8RcBV0xkOIXI2G7RIN+Uti0/Yd5rOJEJVtFD+sR92zmajlGYl1rrp5gNWu31evXuXZZ59lbGyM8fHxe9o9PM87cNuj7bAyYlrLVo4QOyUQJg5nj2mlgWqxWCSbzdLR0UEmk2F8fHxbz2G7kobjETH1dqpmLStTdxshhCARNrClb70j11TM7RZdCPJ1B0PXMIVa7n/ZaPHxXbaVEgjR2ofYn5uCqAEnu+KUmh6OC6Hw/5+9P4+RLE3v+tHP+5419sjIfa2svbp6m5meFV+DzbU8SIZ7/cMgcyWQsQGBNWNhjwDbCNkSEkYyEjaCASMhMELXkkHI17IHzLWH6xkvPTP2eHqdruqtKqtyz8iMPc7+vveP90RkZlVWVlZ31dhAP9KMqjMjT5w4cc77vM/zfBdItEJojSUkQZqBEkwWjcJB0bFwJUQRvLHVRwpDPl3bD6j49uHgO1cFl8K0zdqhgVTfPgi52w45P3nYdj0YGItyKWG+7KM0tIcp39zuU/Zs6iWLOInY22uyt7dHlikq5QrPX53l9e0B7UFCyYOa7xBnxs12p5+wXPfwbDG22jgppssezy9J7rRCuoH5Pp6eq7LaKKMzge8KVicL/NYbfZr9iF6YEiSC5cYEvptw++4GKItUGXdfaUmSTBHnsyb7ERMTHM6cQKF5b4Z+cH+1ZOJ+gVjXEgg0UsJEyaHVj2kPE2aqVs5PsnMDR3O9zk0UeGt3gCbGtoyj8IWpElNlj3fPCH44KcIsMcmpNIEj799IFItFPvShD9Fqtbh58ybr6+tcunSJxcXFJy5b9qhxWkvxcSqLwweJCXiyBNt7BVTn5+e5fv06nufxxhtvnIkxnSrNzZ0+b+8NCGJFwZVcmi5xdbZsCJJ5nNS6OynMzjs6JEo+puTk2YJhlOIIC7CwhHr4AqZAS/keZ04nR8WzGMaKJMmFRi1h/s1Iq04yUXS4MFmi4ksmKw67nYDX1wZcni4yXfEIk4wvDQ9yR1dDsk2UIaQ6ljEHTDPNMFIUGpKNdsi5icJ4AdvpxUSpYr5SGHUQmSg5bLZDbm3vU8q6dLstavU658+f582332E79dnpJdw5MFp2liVwPQsXwVLNx7Yki3X/WGvoQTFb8ZitFogzhc2huZsCRCo46CdMlVxWGgXuHgT0QqN6fmvoYLlVtOqhMkiExsJUwJ4tiRNFvWDRCjIehcOqAZ1J07+V750ocPpbHnkWohit4dqcjyPleN6lFCh9aAOvFKwdDGgOEjJtgB71gs3TC1VmKz6jpuVZwQ8nRaRMcjpXapyYnAAmJib4xCc+wc7ODm+++SZra2tjgMSflBnTn2h18f8do1Kp0O/3H1sr7yQB1WeeeYZ6vX7s+Ge1vrix3ePrdzqUPJtawWYYZ/zBWhulNc8uVIEHt+5Oik6Qst2NqPoOzWGenR5DchrGGoGx3E6VeoDC+AntOvV+ABH3Hz1IYL+fESQZcZqZd5Hg2zZFz8bO4IVzNRZrfq7AodkTIQqYLLu5OoJmtuJwK05pDZO8UjLQYiEtwkQhhMa2LMq+RZwqUq1x888UJQp5RMYmyzK63S47O23oaD5yYYZzK+fwfAcEbA0gIWK2VmSx6rPVi4wPUWLUOlxp+GLDSDFdsc+kJi4FFCz7vs1BN8rY6yVMlT0KnkWYZNzNlSikENSLDo7jYqsYqRVpCpZtYQGOhqJrESRAerbkpLWAo6g7BfoB3LLHFd0Y4jRmrdnDsSVXZ8rUfJc0tYypZf7eawcDXtvs4TuShbpPmCh6ofnO52o+WQ5BfBTww0kRq5Tbg33OFRu41snLrhCCubk5ZmZmuHPnDq+88grVavVPBCpPa32qVt7/EpJE/6tFpVIhyzLCMHxfKLher8fm5iY7Ozt4nsfCwgLPPffcA7XwLMsiTU8XmgySjLf2BlR8m0bRRWsjUdOL4LXNHquTBVrJ8NTW3b3RDVPiTNEo2rx7cOQX2kB35XtIEEIL0gzKroUUemzrcBijOcADHnAl3vdipbXhJiltKqPJks1ePyaIM5SGiYJN0bVRcUarnzBf9bGEQQxGaTZG8YFxtW0HCa0gBa2IUk2mzU5fJxlKQaNkM1txUcq03Jx88RJaUPMcbquAIAzotjv0+n1cz6NSq/Hhy3MsNsygWCvoxjGbQ1isgO9YzE/4ZGh8S7DeDYlSicBApSHg/JRPxT/Do6vliRWr1hqlQGBAKVLIfFM2+p3GtgRSWkwWbHpRQpal1Io2Ba2ZqhfoxUOGZzDn0yNI3bHvVTzx5ORIKLqCZj8iuNvkudkStsw3CkoipCZRitsHRj+wXnRBaWzXqMevt4xivp0/C48jMSRZxu1+i3PlCbwHJKfRe62urrK4uMi7777LrVu3AJienn6sAINHiRHf8kGzpA9aeU8gRoTVwWDwyInpXgHVmZmZ+wRUHxRnUX4YxlnOEXKJUsW7TdN2iJKMQZKAG/L0YuWRHExHp+Xa8h55GQFKo4Thq5wlNEBmZi6MJHTS7ISeyxkOqCT6vRr+6UOgRcm2qPgOUWoSpJACVxjzQs8WWNJisxsxV/eZLrsEiUJlgoLF+GK8szfgbjsiSVMQRqRW5dborm1RyYVQM23M9VYmC+aXSpBkCivuE7b3eG2QMFUrU5ueJ9aS1YrPzAheruFOK+T17S4bfUi9mEANaRQdio7FdhpRsC2KjkWUaaYrHjMVBzFOJA+4UFqgMnmi/yNAyTNQ906Q4Nk+SmkmSh6DMKUdxKRKUynYxJkmBaaqBTwLfB0TRpr5oiKcKvLaRofslH2VQX3KB+xFBGQCbb237/th4dmSatElU5owTPjq62sUVMD83ByNso+LIIozoiSj5FjsdEKa/ZhMK1zLMrNcW1L2BO04P9/3FUb1PlaKW90W5yp1CvbpyhSO43D16lWazSZCiDFA4sKFC48dbPCwGK1TJ1VMZmb3QcX02GPk7zRquz0sHlVA9UFxllZewbGMXUKUstmN2GyH1AoOCRGxCnlnX1MpWJyfKp35fScKDkXHxnMtLME9igYPQsydEBpEbouQKtOvRxsOk350RxUTj5iczA7YVEqjqBUdFus+w0TRHEQUhGSi6NIou0wWHfYHCUEcG/5KpnAsyVNzFazeHs1eRCbgG3e7dMME25QRSAGOY5TIXVtQK9qkmWauatS993sxzVaADjoEnQMc1+ETF6fpiSLNvvE6Ol8zQ3Y3B65s9yJe3+qatqCWDOOUnV5EpjTTZY+1VkC14DBddin7NvNVDy83KxwmitIJ7TyhczLxKZ0+SwouzZR4Zb3LZiegHyjCJCWneyEFCAQlzxCRhRC4toWQDl4ScdAZUEUxWXDY6CUP+E7O8P0LIJNnTE4CK/+Ts5hZ2FIa3poWRMpiLbb49df3qb65x/n5KT5+ZYFG0cWRknf2h/TCFN+WaOBGs0eYKIquRcmBzZ7gnb0Bl2bKx84zU5qDQUKYZGNVj5M2iELLY6TkVCtu91qcq0xQfEhyArPenD9/Hs/zuHnz5tgDanl5+VvW4kvTdCw8/a2IDxITpnI5iyfTSQKqH/nIRx5JhPVoPEySCEw/f3WyyIu3Wmy2Q6q+RTsd0olDFmqmpbPeClmeKJyqen00HFtQLdg0e7F50O7LP8LsgLR44NxHK4HUoMUhcVZBbjz4Xm/efP6kZN7mOT0xHlZJxxcDWwqkEDhSGF8jWyKFwLctpJTUfJswSXlqrsxCvYBvW5QdSHdhbr7KV9da9HOvKWlJkjQjVaY6soWgUXB4Zr7CZiegHcR8490maRgQRhGNSomPXzzH+bnG+LRSpXMC7PHzv3sQsN2NSZUBVjR7GcUkJkwUS3WPkmtTdo2tey9I6QUZJd9ituJinbSQK3FmtFzNd7g6W2Z/ELFBiNWR3O0MEAiGmPmc0jBTcZFo5mo+V2fLvPXWAc9dW6WgI7a+tsEucDQ1Gd7aI1QXgrxyelhbz8D9fcsU5A87ZJRoEpVgIUgzw0+rlisUZMr6TpNmq8WnP3SBqu+y3WlRL7gUPYvdruGq1Xwb1xbMlB2aUnBju0e96DBdMdVuEGe8vN7hVnNImGbYUrA6WeSFcxOH87+cw3fSd5Jpze1ei5VynbJzOhR8hMobadbt7e2NbdGvXr3KzMzME6e5jIAPD3qfD1p5Tyge5GL7OARUHxRnFXF9dqHCXj/izd0eA/pYlhEXXah7JKlmmCqSTJ0pMbWHCa9udrnVHNIOEwqORRKddA7CtGIkOFJTLdr0g5REA6lZ+I21xYNFVB89jgAjFGh5emI8aQE03TjBnYMAxxaUfIsoNsNuxxKEScYgSil7Ngv1AnN5Wy3LMmwBizU/92Sy6OZItRERWWmIhaYdJKztD9huD8kSRcODS7MVnl5doBVmrPdhOZ/T9MOUg2FCO0iRAoqOpFHyqBVsNjoh7SChUXKYKYBV8GhHiv1+zOqkz2TRYacXUfYswkQTJCnv7mekc6WxXcfosmktHmpFn6SK2wdDXrrboTWIsW1Jlik826IfKrqBwnXMt2lLgQb6YYZbMgrjy40ioqa5Pl/B96c5tx7xVnukUC8O1T3yBerMFY4QkOUzp1NuJQ1YUiJOEJYdv0ZrtJJESuNqSLTGtUxbr1aw2esratVp1g96/MpX3mRlskTF8ZFS0wkSumFKo+gwWfbohxkHlqYdC1rbfYJE8cxClQvTJV7b6PJ77xwY5RApkBJ2+zGZgj9zZcrcxbk6+YNCac2dfpvlUo2K+2D18aNoOCEEMzMzTE1Nsb6+zuuvvz6WODrq0v2441tpEggfJKZx3AsZHwmobm1tEccx8/Pz70tA9aQ4S8UEZhZ0Zc7jlX2BxKdacPDzdlAnSSk68hhx8EExIod2goRUKYQWVH3TT38Qukorge9KVupF9u2YOIo5MKLXBjig5UNFPd9bmHnXSclJK3lClWei6AsuzxSpFd3cviImSBRl1yLJFcKrBcc4th4BEIx2e0JAohRhpEmyE+g2GnpBwv5BhG85zM5UsF2XPhIlJI2iZLcf0xrGdIKUt5tDbjcHRn/OtpiuuMyUPa7NlYlTw4vybAsB1IsO9ZJkvWWg5ztOQrMfc/sgQACebVH2LJr9lFfXe3x4pTZu3T0skkzz8nqHP7jTphMk+I6kmSPxpkoOSaZoFF16UYqWGscSpJmRPorTjH6UEiQZ16zDa9KPFVqMAA45D+3I9bItc488BN8z+gLMZoT7k9PRoj5TGt+C6IQxpjkPA7BxLEHRtfEdC9+RDOMMSyTs9WKkgFKpgOOW2RgM6PWaXJyrMTFpZJkybY6VZIo7+xFBBhVLICS8udtntxfxtdsH7PYiSq6NbQlKro0EXt/q8qGlGrWC99CNAhxJTuUaVfdkgv1JqDwpJSsrKywsLHDr1i3+4A/+gOnpaa5cufK+ZcwedA7fyrnWB4kJsyiVSiU6nQ4vvvgi5XKZZrNJrVZjdXWV6enpJ7JbOEvFlCrFRq9HmMWsThR5a69PnCqD0oozkkyxMlc+E/ihGyS0BjG1gsOdVojSBh5c8232h+mJa72VMxq73T46yZgtedi2oBuqHCad0Rw8mdR0mJzIEWPkC+CDo+w6PLtY55mFMqnS7PUiXt/sEyYZti1J81X80lSRwkmQa22qhYNBauRqTph3FWzB1aU5wsy81rMl7WHCIE6p+TZaa/Z6CWutIYMoRQGL9UIOX1fESnFzt4/vGLvw/YHhlIWpQYrVig6e5dILAgZxlnNvIFEpdctBaMWd1pDzk2W6ganIbClolGymSo4BsCiF4zjjFstuL+Td/QFozVzFI1WafZHkpoSCMFWUPZtUKdrDBJBk2iARUw0Hg4Ru2GHNEtTXu3zknMNac3gsGRwNW5DLJkniLDWL/UO/7tF88+TKycZoGTZ7CfokLcYckl50BM8u1nAsiWsJdnNO2TCKcW1BvegyjDKWGyXSrIBwfPZ7fYaDO5TKNbZCiW0JfEcSZ6YiKns2sxUP2xJ8/XaHjXZIvehS9c0164QpZdciDFL2uilV/+z+Sxq42++wWIK6d39yOo1gO5IEWl5e5q233uJ3f/d3WVlZ4eLFi+/bGftonIXD9EEr7zHHxsYGzWaTv/t3/y7FYpFf+7VfeywCqg+Lh4EfhknCerdLlCnWWwH7vYQwVrSCgJpvM11xuTpTYql+NikjpQ1KzZZiTDwF8G2JJxShNquBhCPeQ5o0hUFkMV0vYdkWvk6ZLAnCTDMIwbEyzoAcfo9hFhwtTtfOkxgkoRAwUuqxpWC+5uNYkjutgG6Q4heMsOriPddM5McexClv7w0O5wJKomVqkHCAyAT1UpHZaoF2kLDXj/GOtNXaQ9MmHMYpWpMLqhq9ubIUtIZJDv1OURqCVNGNUrqBsSxfbpQo+zZlT7J+EHK3FRBlRoAVoNmPqfs2rmVTsNuESWaKDaV5twnnGz5XZ8oIIcY7bSkkrWFMmhll8zhTbHdD2sMYmdu1F2xJlGUUXYtemBpyrTJq7FJIhARXQjeB/+8b+7RDRSdIyLKTUXeZ1gilcF2LetGhEyRnJOTen5xGX4VnC+pFj06QINLDn+vcWkzkwI2qb3NppsxO1wBJbNskJ61gtubSGSZMllxqBYdMK1JVouzXOOj02W3uE6SaSrVML7OJkwyFuY8Krk2cZgzi1ABY8pLIlhLf0bSDlKrr4DmP3trWwPqgg0LT8A4h4Qa+/3DlB9/3efbZZzl37twxgMTKyspjASx8q1t57/mM/+k//ad87GMfo1KpMDMzw/d+7/dy8+bNY68Jw5DPfOYzTE5OUi6X+b7v+777DPnu3LnD93zP91AsFpmZmeHv//2/fx+357d/+7f5yEc+gud5XLp0iV/8xV+873w+//nPs7q6iu/7fOITn+BrX/vaQ8/lP/2n/8Rf+At/gfPnzxMEAX/uz/05Xn31Va5evfrEkxKc3sprDoesdTqkWvH2bp9XN7tGPLRqZg+OJbgwVWRlsnjmnUrZtynmqgjVgpULftogoeJA3Ze4EnwJNUdRtMFBIIUk1pKtg5i9fkSmFINY0Rqk9BP1WMVgTwwFpIIH9Ubyog5bCsq+adkdjamyy0eWa3z7pUk+uVpnacK/rwoaXcO7LdN6O3xjQNvmrXNzw0xrSp7FbNWj5FlsdCKS3B5DA5dnSqQaHGnmPqOkJ4QY2zd0gpTtToRWmjgxVVmUavqxYrVRQGnNrYOAfmSknVR+NkkqaA8U6+2IW80BjaLFdMlhtuIaIEw3oZ+anbSUuc2GMhwtSwqSVLHRCsky406bKpNgfFdS82wGYWpGPkqTZQZoMIgyhklGN1ZEGdw5GPLfXt4xqLcHIdYRRBn0g5g0TR9JJcIkp8OZmY2ZV1mWIIhTSp5jbNa1RmcCtEmurtG7peQ5zFVczk8VKXmWSXIaMq1oD0yFGaQZqTJuwlXf4VMXGnzH04v8X9/2NP/PZ+e5bPcoqT4VF5YrktlcADZODUhjvuoT5S3OMFWEEQSRYqbqn9nl+KTYHHRphocjhdHG9azJpVqt8rGPfYznnnuO9fV1fud3foetra33Dec+rZX3JEzQ33Ni+tKXvsRnPvMZvvKVr/Cbv/mbJEnCd3/3dx+b0/zYj/0Yv/Zrv8Z/+S//hS996Utsbm7yF//iXxz/Pssyvud7voc4jvn93/99/uN//I/84i/+Ij/1Uz81fs2tW7f4nu/5Hr7zO7+Tl156iR/90R/lb/7Nv8n/+B//Y/yaX/7lX+Zzn/scP/3TP80f/dEf8fzzz/PpT3+a3d3dU8/l7/29v8cLL7zA22+/zXd+53fy1FNPvS8L5EeNk1p5qVKsdTrsDgdoNP0w5W47zAm2DmXXZrFSwBaSzXb0SDeFZ1tcnCoRZ4qiY1FwJO1hii8FdR+WCopZH6bKFtVSiYLj0ii5nG+UmK94NMoOU56LRBKmmQE+6AcPot9/aLMa5yKsZCdCCMc/8W3BZNFltxed2DeyTuH3RnEEwFdeXyNMRn+cPx4KSA4flYpns9EO6UeZAVHUPJ6aK/PUbJmPnquxWPeZKjmEaUa1YBOmqUkQmQFhxMr4La23AvaHCQdBykFoiM8WGtey+K03mrQGqfnsygARdD7HSbSxamj2I4McFMayoeQ5HPRT3tjuc+cgIEiMKrUQgomCjW9BGCeEqcJ3JI4tyJRCChhGilRB0bOpeA6uZeR7sszMsJSCLNWEmaYXZBwMDXDmtD10rCETRrrp0cN8bqmhVrAo2uA7ZoNQ8W1KnoUnzOZqFK5tMVF2WaoXcp3AlPYwIVNGpsoWkmGSkqQpb+/2+fJb+2y2Q+br/rhVtzRR5PrFZf7spz7CRxbKEHSJk5Q0SUmyjHaQMFF0WZkssFgv5Dwpozg/WXT5xGqdwgniuo8S28M+u4EBYo02ro9arUxPT/Nt3/ZtXLx4kRs3bvCVr3yFVqv1ns/pWy2LJPRjSnd7e3vMzMzwpS99iT/9p/80nU6H6elpfumXfom/9Jf+EgA3btzgqaee4sUXX+STn/wk//2//3f+/J//82xubjI7OwvAL/zCL/DjP/7j7O3t4bouP/7jP84XvvAFXnvttfF7/ZW/8ldot9v8xm/8BgCf+MQn+NjHPsa/+lf/CjBf5vLyMj/yIz/CT/zET5zpXH7oh36IRqPBT//0Tz+Oy3GmCIKAr3zlK3znd34ncNi6S4+UIDu9iK/dbjNf8Y5VRoMkI1aKb7s0caLK9INCa81eP2KrE3Fz44Dbe12iMEEBTqFIwXNJEk2mzPxjvu7T7Ce0hjGXpktsdyO6QUw/S9kfJI+5hXcE4TdSDDgpk+Qq1QKTbJQ2f3Vptkg5h9d/bHUCSwhmq97YHuL+iwHtTpu93T063Q5oeDtr8Nvv9mmPfKryNtHoPKSl+PZLDZ5aqGCJPJnIEQpNUPFt5nIY/xvbPXa7MQfDiP2+SQiVnI/08kaXfmQAEbaU9IYBSItqweHDSzXe2unx2vbw8EQzcpjbIeJtumJ2+hemS7nm25Db+wGTZWe8YF+aKXFttsJUyebGdp/feGOPXpCQKI3W4NsWloTmIOHSdImL0yUOBjFferPJQTCSq9IgdQ7t1iAsfFtQ8mxag+RU/TpHGhWN6D0lJ/AE1EsSS6QsTlaJM+gMTLLpRxkZpuLMMk2j7DBd9pkqO/iuzXYnwBYS35FEmaYbJPQjUxEqDWGiWG74/L8+upRzlI7fJ1pr/uDmLV5b2yXMoDFR4/zCFBXf4VZzaKrJwCQrIeCFlTofW514bLOWab9EVVh86Utf4tOf/vR7Pm6apty+fZtbt24xNTXFlStXKJXOznsEeOutt4iiiGeeeea+3xnrefFY3REe24yp0+kAxq0R4Otf/zpJkvBd3/Vd49dcu3aNlZWVcTJ48cUXefbZZ8dJCeDTn/40P/zDP8zrr7/Ohz/8YV588cVjxxi95kd/9EcBg577+te/zk/+5E+Ofy+l5Lu+67t48cUXz3wuZ+ExPe4YtVqUUhyEIXvDIfqerb4tJLYQJEozzHXbRtSheuFQBueskSYJaXcfmntc8eD56w02I5ev3Fjn4kwVW1istyPCOCVV4FqSoiPZU5phbOYZqYJhoJ/cXOmeZHBfZBIslVcLAoSm5JhyqDlI6Uc97rRChIDZsse3XWpwrnHYt0+TlL29Pfaae2itmZ6eZnV1lZdfeZmVyQru2hBIzVD/nvW0bFt0goQ3tnqEqaIbGMM+gYGj1wo2M92I+arH1ekS9YLDS+spmU4MUsyRpi0Wxgb6DAzzay1R7HUjgjjDHXNhDJ9svJpKM0zJMEi72/tD6kWXOFVsdUKKrrmngiQjSuHl9S7dIOXphQrX5iqst0P2B7GZKzoWjaLLN7d6eK7N5Zky+8OYzdw9dxxjt0Vh3h9IM80gSpGcLqxqSXFCxXR2ikHBlzR8F5VlOLnKuc71GEteTltwFZlSaCGxJJR9h9bA2IOUPJtumJBqqBZslNY0BwmeZVqDwyjja2ttHNtsaI6GEILViRJ+WqYyPcPm+jpue425lRVqC3Vu7wcUnYzlRpFzkwWWJwqPLSkFccaNfouKEAgh39dxbdvm0qVLLC8v8/bbb/N7v/d7LC0tcenSpTPbaTysYnrcPKrHkpiUUvzoj/4o3/Zt3zbOqNvb27iuex+2fnZ2lu3t7fFrjial0e9HvzvtNd1ulyAIaLVaZFl24mtu3Lhx5nOpVCqsr6+/xyvw3sKyLDKtudVqET1gUFMvOlR8i6+ttWkNEuIcVWZJwfOLVYJAUS49SPbFhNaabqfDXrNJu92mWqmwcu4c9VoNhWD33X1mPDhX89nopviOxLUcNtoBYaKQ0iy8SaYQmAUpjI11BGewzj57mMpgZEt3amQCyzU27RaGkb7fj0kzhV/1mSoZDbvNTshv3djj+z40h53F7O7t0mq1KJfLrCyvUKvVxgKdQgguTxfwHCtXk7j/bW1LcucgphSk2FJgCxgmioIjma0WSZTGlYK9fsRk2cwCu2FK1bfwbIuCKwlTRZoZfb6eMl5NaZbPTID19pBBrA7bmOOHXuRruklOAsFON+bVjS6uZeYsfo48nCx7KAXtIKbZj/jiDWPLkWmzsSi4NgVHMkwSOmHChO8wjDMOBgnHZ/c6b6Hmek0jDrQ+snc4pRgSaGzrXsj42ScIFd9lruogk4QXLsyQKs1Xbx2wP4wNwjHTlHyb9jDOK2jBMM4ouPaha62waPcjHCloBYmRHbJdMq1IMs3+IOZWc8BivXBfda20xrEsLs1Pc2Fukp3dHd59e41CschzK+dw/CKOZfhVjyNSpXhrp896OySIU7IkRbVSKu80c0K8YHGiwOpkkcYp1icnhed5PP3008cAEhcuXODcuXMPbdOlafot9YR6LInpM5/5DK+99hq/+7u/+zgO98cSDyLYPskIs4ydOGY6inDdk6GdOb2D/UFEkhqJIqUVEkF7mPDu/pDnizUDn71n15IkCc1mk73dXZIsw600mFy5TL1UoF40UOIkzkgScPNBvW8LsswoWu9akoNhTNW3EQIOhjFlxyJMFbHKJVmVIJOnI+bOFFqDkgbA4Ao64b2146HNthAG6FCybaStqXg2niPZ7oQ4tsVKI08uwJztcWuny//8+g3OlzKmpqZ4+umnT2w7CCGwEMwUHJpWTHBcqwlLwDBWuDbMFH3CLEMKSTeMCFBsdkIKrsVGN2S1UeTOQch2N2QYZczXzOyyH2UkmRFKDWLjF6T0cQfWzU6IL23u5QXlZwm5CrzvmuTZDxOKrk214DCIFZ4j6QxT4sw40VZ8i1QZxGA/SumHBr5dcIyvk+9KfFvQ7IdESUZrGDPMzQ3J7kmMmQDL5MssR/mdFsFZOEwPCBszz1uuedRVysdXGrSChFv7Q5JMMzXlMowzmr0Y17aoFxwmCo4R8fWNlFcvSpkqeRwMY/b6sZmvuuZOKjgWRdcizRR7vYggTnHusWDXWptZsDKzvJnpBRoTM2xsbPD6668xNTXFysoK1mNatG83h9zc6aM09MOUrVafW82Mr/7WayyVKlQ9h4mSx5XZMt9+afJkV96HRLlc5oUXXmB/f5+bN29y584drly5wvz8/AMrn4fxmP7EVUyf/exn+fVf/3W+/OUvs7S0NP753NwccRzTbrePVSo7OzvMzc2NX3Mvem6E2jv6mnuRfDs7O1Sr1bHGnWVZJ77m6DEedi7fCrPAo7E3HNIcDlEClMqAkxNTN0hp9hNmyj6+LQlSxTBOGcYZ650A665kqZ4jgSyzw+v3euzu7tJqt6mUyzRmF1kfSraHCWonwBYhczWP63MVXCnxLYtECYaxESwVUtAcmCFv1bc4GKbMVHyk0HTD7LARI8z8QCtQ7yc5jQEO4NoCy7IoexmDSI8Tkc536L4F9ZJDteBQ8iziVKOFIlGGczPhWdiWIE5igmHAcDgkiiVuqc7zH3owdFYpTXsIX3qrzVY3Ij5hxc00CK2ZLzrUPIegr8Ay7zvILSoqvm28lBBGLSNMKXsWidL08mH8/jA2EHDgPlCmhnZfcVzo594QOECUZIQpRh274LDRCWgNEzTgWUZ4NkoVQrh0gwSkNH+TZBRdGykstDCL/zBR3N4fGt+pTJFlmLnWffBF83NtnU2z7v2EZQkWqz6fWCxxcBAhhKBRdPnoygStYUxrmFB0JBemi/SjlEGkqBVdWkGCbQnKvk0vMu3niaLDejswLT8tsS2Jb1s0Sp6RnNIa5wTllJGtudQClQmkheElVKYJA48/3Nzl5bVv8OyFeS6dW3pf0OwkU9xtBYSJAZdkCtphSpxCNwmx/AJVv0CQpKy3Al7d7DJT8d6zieHk5CSf+tSn2Nra4s033xwrSExOTt732m81+OE9JyatNT/yIz/Cr/zKr/Dbv/3b97mwvvDCCziOwxe/+EW+7/u+D2CcnT/1qU8B8KlPfYp/8k/+Cbu7u8zMzADwm7/5m1SrVa5fvz5+zX/7b//t2LF/8zd/c3wM13V54YUX+OIXv8j3fu/3AuZm+uIXv8hnP/vZM5/Lt2rGNCLMDnKbCikt1Cm6JVGakaQG+dYKEnb7MUoZmRWtNVudkNc2e3x8pUq3vc/uvqmOpqameOaZZ/A8j6/f6bDXD5mueDhSEKWK9YMIX9pcnyuzNOHze5Ggs9HHdW3COKMfZ8xVPGaqHlNll4JjsdEJ8WzJwcBBZTFZzotipFn3yMlJgxIILQ6ro3zGbkmJbWU4thHvjDKNVnBxxhgkJpmBrPei1PhACU3ZswmihJvrTYTOmCx5TDQaRL2UxakJuqFiEMdYUtAoOmMx1TDKeHWjz5c3JV3VpjNMHlgJOMK0V9tBQm+Y0o8TummKysyAPzLeH6x3NOdtn1Rp1g5C4iQjyjRxajToTpzPaXM91Bl2n5YUBJFx5k0yzcEwph/lBN5UYRVsksw48e70IgZRhpTCzI602YRY0mx8Fmo+COP62g4yssSQSh+oKDGaOY00hx5rKIynl6Zg2YSxZqsbE8UGrOA7kmszFRxL8PJGhzDJcqFji6KncC3zGdvDBK015yZ8hol5hhoFl06YkGSaIDaISd8WdAPFTNk/kXCtlEJqOd5AZKnmm1t9bh308WyLyek59jt9vvZuk93dXa5eOEe9MUmzH9MJEixpqtKJvENxWiSZmSN3wpQkNTD+g0FMoiCNEt7c7mLPCspWkVQpmv2IQZydzQLlASGEGAtQr62t8Y1vfIOJiQmuXr16TOXmW+nFBO8jMX3mM5/hl37pl/jVX/1VKpXKeFZTq9UoFArUajX+xt/4G3zuc5+j0WhQrVb5kR/5ET71qU/xyU9+EoDv/u7v5vr16/y1v/bX+Nmf/Vm2t7f5R//oH/GZz3xmDNv+O3/n7/Cv/tW/4h/8g3/AD/3QD/E//+f/5D//5//MF77whfG5fO5zn+MHfuAH+OhHP8rHP/5xfv7nf57BYMAP/uAPjs/pYecyMgt8knES6k5KkVdMJ4fvWLi25GAQ0+wbSwKtoZXFOJbEt+EP394i3L3NuakSC3OL1Bt1ZC5R1AkS9gcxkyXXACU0+NKi6mq2OyEXp4rGKlwYAiVA0bWZKNpMlz1cSzJIU9YOhry80UWpXJuSfB3NRyEjWDPyjDOnsWLA8RGFJYzIrE6gUXIourYBBgiNa0s+vlpneaLIW7t9LJkZQIaGdi8k1RkSQVdLpPDo9wU7YcjqlPE3+urtFklmzq/m21xfKDNd9Hh7Z8jN7T79FOpls8smPXlVzjR0ohSUUWnoBYosBwWMHD8OBgmNouBWM2AYZ/SjjCDOSLM8kZ90eU61iLg/LCGIErNh2e2F7PUjU70yqjIltqUYhNnhBkLpXIHBkKbjfkKYZqSZouzb9OOMMFIGyWZbhKeopQoh0E8kOUkkmiKCoi242xryezrGJ2HwdpMLUyVWp4pcnCwzW/E5CGKU1tQKDkGc8m5zwF4vZr0VkCrjSBulCq0hQ43NEBOlWN8PaA0SLs+U+Mhy7eTTSTVBAje2ejT7sWmPdiPTLvbN/Vsr1Nlo+diFlHdu32bzjXWywgSe66G1xrUtLs+WuDhVOjU5ubYgTjW39gYEqSJOMvqxmaMRS1Qa8+pWh6lSxNP2JJYQj80yxLIsLly4wNLSEm+//Ta///u/z+LiIpcuXcLzvP91Wnn/5t/8GwC+4zu+49jP/8N/+A/89b/+1wH4uZ/7OaSUfN/3fR9RFPHpT3+af/2v//X4tZZl8eu//uv88A//MJ/61KcolUr8wA/8AP/4H//j8WvOnz/PF77wBX7sx36Mf/Ev/gVLS0v8u3/37/j0pz89fs33f//3s7e3x0/91E+xvb3Nhz70IX7jN37jGCDiYecy0sp7XC6298aodXfv5ERKa+ySeVJUfRspzM52GJuyXmMM66TOEHFG13KwJxa5ds20JYUQKG1mTmmmSVXeptBmJgRGLmaQL5bb3ZCiI/A8iUFJaxzbZq0VUi/aLNR8vrndJ80leMLUcF8SzObZ0oZx79gQZcLMyk+LMRT8/pgq2yzWS2x2I1YmfHzbIlaaJFVMFB2kkCzUPJr9iJvvdojCiCiOKVg2CxMVNocJw1iRKUhzO4Kia7O2HzBb8Si4Lkpp9vox31wf8NyC0bYDM+cxFiMP/j7iDMqOJEwUw9i8TuZzH9+XlF2LON/59iKjnGDmSofHOL7v1Ic6c48Qw8TMp4QGS0scGxAyF/M1LrSWEITJEJUqNPebN5pWomajbWZjthYGBWoJWv3TG3UG+PD4KycBVFxDoO2GKU6ckpV9JisSLeD17S6eI1moFyi7NlXfRuVaihNFhzjT7PViHFtw+yCgH8Z5ZawZxiYxS6EpOLbRH7QEF6dLTJSOt9KFNryxTpjxxn6ME/UouTbbnZCNVkDRtVh2Cyhp1ouSb5NYHkur17jxzbuI/R3cWpmZqWlCJXh7d8BU2aVeePAsahhlBHFKK8jbuFoTxYAS2JaZ6QVJyu2DHq4l+I6rU5S9xyve47ou169f59y5c7z55pt8+ctf5vz58//riLiepXzzfZ/Pf/7zfP7zn3/ga86dO3dfq+7e+I7v+A6+8Y1vnPqaz372s+PW3Xs5lydVMd3burs3LClzhe6TQwjTwtBaobTON/LKoICEoD5RJdOCfmIgvLZlLCskEiWMQoFvW2wcBGOiZK1gk2rNRMHBdyyjgB1q0iTCNNFNpXUQpFQLFXa6ZjBcK9h0A0MWLXs2Ik7H7SLXlvi2SXZBkqHkIe3lMPSJEOxR2MCnVsp8+MIs/7+b+4RJRpyZzzpZ86i4NpbQ9Fv79Ha38VLNuZkKsajTixSOLUnaKSXPwhaCONPUfJvNdshS/bBVI4Vgtuix3Y1MFZppIyOjc8WDh3ynl2fKrB0EtMPUVB+ZRmuBiqFPRpaapFFyLTLNfS2x8aOjyfXdTlvVT4ZWZ4AnIVHkNgsCJY19BlqTKUXJd6gVHHa7EScVahoIYw1CIyNJKsxnIdGnTriOxSg5SX1Ux+pYPAxSfvRDCWEAOLZlIYTEQtHqDZh1beZsiBLBRjtgoW7g/0qBtAQKs3m5ud2jNUzy71VR9W2CVNEOUpN0ZV7tAUsTBbzcgylM1Pj+GCUlgI1OzCCGp2t+LvNk9Bd3ehGNkkvRs9FSkWYKr2CzN0iYnZyk7k+xt9fknVvvMjnRILRLtIfpqYlpvR3guRazZQPWGEaZAT0KMdYaHOROAAdBxEavQ5BMUHiMmnijKJVKfPjDH6bVanHjxg0GgwEHBwdMTU3dt3F/3JYX8IFW3jieVGIaJskDkxKAkPKBFVOYKO7sD3jpzoEhMmbauLHmbP4o1Wx2Yi7PFPEcAz238+VHa43UAtcyLZe3dodYUuBaktsHQ+pFh2fnq1jSaKKt90HKGCktUq1IM5NU7xxYTBRdXNtCKkWqVC7sqY8sIsZWHUkOt7VIlSY+OtkfLcKnhLRgmBrriecWK7zbHFL2DKw5iCK2mk2mxJA+JSanZtBVyXy1wF4/phcZs7dhnJEpQbFgmQpBGOuJXmQqADGah+VocNsSlD3LQIwd6IWnVwpurq5d9myWaj639wNSnRFnxhpRZ6ClwkcYoMiojXYk1Pj/eEhSgtOg1YkySS5MMjzbIs73FULCbs6H0hhFdcnJCSLLcidjYRx6o/ReedR744Rd8wg6ysnJ6eFJaQRJFzgCM2OSRiFcSodUCiKV8e67t/AqE/Scuvng+bVTmUlOd1sBv//OAUFi7oMgUSg0jpCmsheANM+EgehrGkU758KZM5FaHM6TlKIVZpS9Qx+iim9TKzo0+zHDOKXoWoShaREu1ApstAMQYDsO8wvzTAQT7OzssN1rs1xSnGs8mOu0348p527IjpTcjQIsoY+jNnNEar1gs9Ye8rX1HT61Mo/7hKqZiYkJPvnJT/Jbv/VbY+ufq1evHjNU/RM1Y/rfLZ5UK6/qecypMtuDk5OeJeWJenmtTp/fv7nJ2n6fYWRkaETOJ0pH9gAYFF7Vs2mUnPtQRTrTtPsJcaq4NlumF6bEmaZRdI6td61hTJCCY2tQGWn+FGgNe70YpYzF+34/YphDnNGaODOtqjg1I+s0UEghmC65IARr7YAx9+VhSQmz5O3kXI1rs2WU0tzeaXG320NkKRfnqrxw8Skq5SIb7ZC9ux1SrY1EjW+xthkQxhmebRsPJglpalqZgygzaDJ9WIU6lqRWMNetG6bUXOgocx4PqpouTRsSZqY0Zc8yO/W8R6bFSFBUoizFyTnuvbXuTopMGeWLMNHY+aZAY5HojJJr4VpG8cCzJXGWHUuQEo3KDDzeFqaF53mCOEvR6gxK4PfGKcnpVKrTkVnj6DCWFMRJRjdMjXOuo9kNHS7M1dhrtiDosD9tMdloHEtOf7TWph0kTI6fhZRemDDUKSXXJlMalWlsYeF7gkGcYkvfgHtsC6HE8WskRJ7MDz+P50gWawXaeVUWpQaIdLFRYr5qVNu3uiGp0thS4Bd8puYX0X6PwcEur7xywOrqKrXa/TMtzzHw9oVKkTDUDEop3SAd34uWMBViqDXrrZCC2yfNzNl98gkmJyFMF+ajH/0o+/v7vPLKK1SrVa5du/aeTVIfFh8kpjwqlQpaa4bD4WP1XAJoFApkWrM3vB/1J48IuWZpxv7BAXt7e2y0Q7bjAvXGFKrbRWFUqVW+2xfASBHUsyXnGoVj64GpDDSdQYZOYXHCR9fM7ksKaPYTmv2IpQmfrU6Uc4NM9SSlQCKIM6Oftt4K6EdqvJZmGoaxzoVTGatbg1H2HiQZCzUfvysYxvqhVYEEfMdgwpXWRGFodA6b+yy5Ds9cnmZuepJa8bANMl3xmKt6bHYiSq5F1TPKz7Zl+CYFW1L2LCJt5itV12GrHVHyLdLMVBkXpoqG+1J0sKVg0NwkK5RIFGy243ss54247TMLZaSU9KOUTpQgctv1Y3xcDVEsEVLl24fDn491/x4QrjAac6eHQmLaUmmeRNpBim9DreAyU/R4aqFMJzQL866EFE2aapLMtOtU3kJUQJxpbMuImQ5jRRyPNkoPRlmeeJ4PqZzuC00OST/8ke9YRn8uNT5VqVJ4liTTilvtlEvzc1yrw61332V7e5vz589TLBbphwnrzQBbCHb7BnmZKnPPJokGByxLkqUZClMd+rZkdbLIpcnyWI/w+McRTBcEd4cGQOHZBoKv0Dy7VOPydAlLGiHkesFBSsFC1WOv5rPRDnFyyL4Q8Oy5aS5Pn2N7e5sbN25Qq9U4d+4chcKhIslitchOK6bkSmarPru96Ng9OJoRCg29KCFKDefsa7dbpBq+bWUO7wl4JimlUErhui6rq6ssLi7yzjvv8OKLLzI/P8/Fixcfu8boB4kpj1EyGgwGjz0xAUwXiyit2A+CYz+XQhCGIWu312ju7+N7HtMzM4Rlh1ffbnF7NzAtGXX4DI988zSm3XZtrsxs9fDGkDp3n8VAw3thSnGYUiqY2QvkkwthuBNxpo0y88g3AtPLTjJNpgx0WuXv61gCpbTZ9Guj5uzagiDJFzFhWiGeZbFYLvBuc0gmTl+oRr/SGkp6yDe/+Tr1+gRXr16mVCqfmNdcS/DsQpWJYsBWJyJzLS7NlIyXkDDouDjVWEJQsR1eWKnh2xb7/Rjfk1ydLbFYP1QZn616XJmwWF6ZYK5e4Xfe3qcfZcbaQUPZN9VVP9bMVSTnp4q8sd0DIUyrMTUSSbYwFYzWGEPDEUoxh4Lf+2GOttcEjFUSTm9/SUNuzq8/wlRPUWqU1D+2OoHSmtYwwc49kZ6aq7DbjdnuBGSpQIvjCTNOFf0wNfBoMtRDEA2OLUiTE9p+9ySnB1ZLSt+jamHCtQSOLRHSVOJJBp3IQMhrrmah7nNttUG4OM3m+jqvvPIKs7MzVCbnaEcpAkHRlqRKY0mBJU2ruVKwOT9ZNP5J2gAhPnKuzkcWaninmGxOFwXKdmkN43xWaBL4MwvVsc36+CMp8C2b5xdrzNV89vsxGuNaPF3xEFKyuLjIzMw0d+7c5eWXX2Zubo6lpSVcy2G+4nN5psxLdzust4eEyXGPtKP/Nt+34txkiSRTvLPXZ7bS4sJEnYL9eGdOI6HpEfjBcZyxpNubb77J66+/PqbdPK74IDHl4fs+juPQ7/fvkzd6XDFbKpMpTTsKyTLFwcEB3V6PLEuZnJzi2tWrFEslhIA/eG2Ht3eNwV2SHS4Aoz2sbZm1zlglpONfypEStdas7Q95e2/AZiek2YuplRwWJw3STWnNdNUjThUTBYeibf4uzDRxZnrmiDwR5ds2R5oKCUsitCbIF6aiZ2NbyrTHpMSVgkuTBcpzZYIkZbNj2oEPGpdoTMut6GQs1cs899wlHOfht6bvSCM8OlUa+xttdwK2ezGpysjycmK64nFhqkSjaFQBBCcXcUIIpBQ8t1Rlrx/nEOwijiWMyV+mWZ0wROe6b2MLzW4vRmiBLTSWNHOLUetFaDNzMuv7/VBwcc+/NeSoy4eHEOC5gjTVBurvWwzijIIjmSq7NPsxSaJo9kP6saLkWFQci20lcSyTsLNMGwUHBUkKapBScKBa9tnqnw5/cCyLKE1Ptg4/kpwsWxxSCuAwQT/gZrCkudaZ0iap2pKKC/WCuWd3exF/dKdNexjjWBWml2oMutu888prJKFDmkkmSy7SNu/ZHiaIAnzbxckxEdWSguWJAs/M1Y6pk594PkJzfbaIU27Qj40M1WTO6zsplDbJaXnCQiB4e6/PRjvl7b0hjZLLtbkyE0WXixcvMj8/z61bt3jp699gaXGZ2blZ5qoeviNZnigyUXR4txkeq1s1ow0pFB2Lqm8T55vPYZxyu93mXK1O8TGbBML9CufFYpHnn3/+PpuixxEfJKY8Ri62T5rLVBWCdzY2WdvZwXUdfN+nWCxy7tzK+DVBnHFju0cvzLCk8fVJjqwACtNOK9hmIb2xM+C5hRpubmYHsNePeWO7T9m1uDJTZrsbstuNOAgSzk0VuDRVYrbskWnNTMXlXVvQiRWphlSZhONIgWdbRFma+9nk8GTMzjbIIXdF18a1NYgMlShcT1LxbPpRxv/j2Vm+9NY+N3aGZsd5z3okc9nsetHiQlXi+cUzJaWjIQSUcvuJu+0AtMaXEukaxYWCbdEdpjSKzsM7TFozUXT49ksN3tob0BomSAwEea5ibLqlMMP5asEzytmpUZ4I08MhtQAcS5Mk+Xdyslnu+Ps6Mtt+mPwcYKzt0zyxCAFBmIAwskwHfUOo3elGHAxTLEfTHaS0g4Q41Xi2eQ/XMqTOLFdqFxaUCp6R7HlIYjqCF3jwC+6d141njQ/+ywxNybHZ7UcUMJW3Lc0RgiTj5fUOcapplByCVHGjGbM6uUBvcMD+sMkggYNBTNGzKPk2ti24MF3i2y9P5cAYTdW3afjumWbJSmlsWzJVcZnibLJDSsNBN+G1jQ5IwVTZM+Kx/YhXNjI+vtqg4FiUCkWevvY0rVaLtdtrbG9vk1ZmEQIuTpd4fbN7371w9L9rBcfM4zKFLQ0oItOa2502K9Ua5cckkzSCij/oep32u/caHySmI/GkElOWZWZutLFBr9djenqaievXEZ7H+vr6feCH3V5MN8gMqdQy2nT3xghBpcnYPojoDBKmy6a1ECYZr2/22BskLNV85ioeNd+mF6bs9iLOTxS4Pl8xg/MoI8rMLMS3Ic5X1hEvSeZCpREjTTc9hq1bQMGWpGneg0dgeTYlx6IdpMxXPYJE0Si7XMiUYfBnGZZl0FeODUK6WFJSL9qkOjbipe8hhIDliQJfv9OmZNu4nlGgrhUcagWbO80hS/UCp7XgjfSR+fzTZZe6b9ENEySCN5sDWkE6hjGDUabJtDZ27XmWGbfmtEYl4rDtOrKtOCUk0Cg7tIcJp1CpzPGAMM0h+RJsy8ITmv4w5otvbOO4Lt0ow9KCaKjJ7GSc9MIUHJFS9Swz40zMAH2m7LPcKBjQyX7wQHO/gm3Iz1GSkdw7iDsSlhBYQmKRko6HcKcvYN0gRblmE9QLUywroxtotnopjpPh2xYXpzJKjk/ZM6K1f3C7xU43plz0KauU9iAliFIKtsWV+SpX58tGDNmzDaL1EYAnWqnx9/0osdEOSRKYm3BBGKHh2arHViek2Y9YmSiOIekTEw3q9Trb29v83jfX6SiXycIcmda4EpKjqLz8CtqC3Pk4oRemXJur4ORKJkpr7nQ7jy05favliOCDxDQOIcRjh4wPBgM2NzfZ2trCdV0WFxd57rnncBzH3DydDlLkQ9oj0Q4Sio6FlIIs5y/dG7ZlHi8bwW4voheYxLTfj3h9q8cb232GiSHsTRRcVhoFyjXbaKPlBEYN3GmFhsPhGLWFum+buZLS+LaFFOA5FkpnhpOk85aXgJJvNNrSTFO0JXMVj9VGgVRrPrJcpRtm7PSGeBIsFVOzU/oYKLdt2/SiBDSUbGMm1wwVM7nmnP8e7KltATNFjynfWHTYlmS67OLZJsEEUUbNOiRk3htCmPlZmhpbdCmgUXKR0mJFwcFGz1QceZekOYgBgesIpDLkWwuIY50rDRwuw1KDzDTSEQbmPfo5h+3ZiaLFRNGhNTi9WhldmWPVltaUCg6TRYtuP8SRKavVClFmTAUdqQnjGFsIUm1AN1rYaK2Q0lQmQkI/SozSwCkl23TZY7ps9PeGp7RxLGm+k0zlQhpn2FVrbaD4caYZZhlJYsAlRdtUd0pn3NofMFX2DIlYCjbaIZaEpXrRGPlVoNcLaAcBvY7AW6zwB7dbDIIU15KsNEqsNAoGJv6QULmI66OGsV83SD+de1mZqkKQJLnz7pEQQjI/v8BHrDJfev0ut27dRrolfAey2IzjLJFvfDQUPIswVuz0Iq7PVbk4ddxfSWnNWrfNcqVG9X0CE9I0PVX14UnEB4npSDwOvTyl1Lg6GhkUPvvss9Tr9WPlrhSC5WqVdcchDMNjx/BsyXTV5e2m4SqBuSlHZFWJeeBVZm5QgF5k9MDe2O7TjzKWJnzW2yFl16Y5iPFdyWw+rC25FuR9/61OSJBkVH2L6ZLALZRYb4XcbQekCpLMDGA921QgZc+mXnSMzUPFZxCmNAqGyFkvOAyTDEsKar7F19/ZZW2vQztMCZSN4/k4KIJIYaUJYaLxHcEwyZCpoJIj+na6EecmCygNraGBu3u2pP6gVpw26gsW0riWBkkuz0NuOWHTKLmG06VyGagjyUkpI+SjtSaKIqCCtOSx6mi+XqAdptw5CMmGCRpNlBqofpyZ9NINEpQyUkBZlldUypyflRM7RWaQi6PvWWMWGtsSTJZ9Zioub+8OOS0KDni2TSdM840CjJqABc9nolRAhUMOuh1iZeGoDFfYrM5VuN1J6UQ530ubytvCDOgtYRLIfj8iOSUxzVY8XFsihRgjA0+KNNM4jiTRFkLpfIF+yEwn13JMVTa+35U2KuVSZri2+Y5bg4R60SFKM6JUMVl2maq4WFLQi1Jcz8fNJMMo5sWX32ZuepKZyRphonllvUOcKq7MPhzkpJQ6UwK7N2q+zU43BByDkBWaLDPzNf+U6mNhoszVlTk2DiqEvQN8kdHR1viyjVC1FyYLrE4VeW6xxtPzlROvq9Zwt9dhUVepvw8Tv7NUTB+08p5gvB/ri+FwOK6ObNtmYWGBZ5555lQPE0tKlisVur3esZ9Plz3mqj71osN+PybLDtUCzNhYgzZw4Ypn4doWlhS0w4ROmDJd9ojTjPYwpZs7dm62QzIFS3Wf6bILCIRSJKmiNUjIEsUwhklXszThkWQqn53kemC+zepkkdmaaQu2BwnXZ8vsdGJTOQjB/iDGQjHjRrx14w4bTUEifS4vTRIkitYwAWLaQYItBEUHCr6FKwUzVZckHNCLjDjlbNXj9a2egczmnJCZqsfTc5X7qimpjWXHIEoJUyNq2ig5uJagEySs7Q9ZnSyOnX51rhaQqlxRI++TTE9Ps76+ThiGrJxbOdbCsaXkmYUqc1WffpgihKAfJez3IwOAwABPwkSRSI1wjIlde5iZLp86nLVIDZYjqBQctIbOMCZNNa1hjG/dD1u+/74xlWzBlWSZmZk4tjGU7AUxli0oorAFtBNNlEmsTBAexDiWxULV42AQo4XATSFMjUpGHKQEsTLUAA7vt9H5WIBnC3zXYq7mc7sZUHUVnTC7n/eVl4zGY8oc4bB6ePAippRR4fBTi+CIjtOoWk9SRT/KjMaf0nSGKbWCg9YGhTdZcQFNO1dw34schtJB7LSwwh4zc7OkluSNrS6zVZdawSVVysxfBwbROV12ma6Y+aHWCvEeKqaFesFQProhNd9BoWgPE2YqhXHL/aTwHcnzSzVqBYe7LZfC9h1KCYT5Bkda4NkWw8R83qWJwqnXU2tY73XRaCb8wgNfd1p80Mr7Y45HrZiUUjSbTTY2Nmi322Ovn4mJs9srO7bNtOPgSIskF3OdLDs8vVDh1v4QWwqauS23hUZogSUlriUoOhZlz6FWtFmuFwhTozQgMb5Nq1MFmr2Y3X6E1nB5psil6RJ2TsRNleagE7O2PwStcC0IVIBjS+bqPkt1n0bRYaMTcS7XrQMjUlp2LRZrBRZrBXa6EZvNNoOgjZ0MmSjVmb50kbfSHjv9CMeSuLZF2bUoOJJawcKxjBPs/IRPuWDjOxYHByG7gSLKNDd3+2y0g7GQbJQqNlohrpQ8u2hIfQIgO1zId/sRni0ZCMHt/SG2Jaj5xiKj6h8+WEopox+Xt1ikNFYbc3NzNBqTrK3d5pWXX2FlZZmp6enxTEIg8jaWWVi6YcKFqTJx2qPTN9fEsyXd0KgGKGV2t0ofJiWBGVI7AsLY2C2MQBCDMGM9O149P+i+izFCq8PMyCJJwJcZrXaAsgWLyxXsUpW9jR79KIZcMb7gWhQSm3NTBRYmimy2AzZaIb0wI8qMJQb6MCEJzGew8s/h2sbDSClN0bMARS/KjuvwKY3IW76DWB3TCXxYckpziaVeaNxxdd6+ksJUmmFKrhlpPJSmKx5TZYev3Gqx0zXf/zvNIe1hgicFQgliIdlTJfxE89ord+lrC2W57PYiPnm+QaoU6+1wbK9ye3/A+ckS1+crqJzX96hRKzh8aLnOO3t9OsMEqQQXamUuzJfGs6AHRcmzeXqhiu9IfseGy7M+m52EOMlwLNBS0AtTojQ7s4P1Rr75fS/J6VutLA4fJKZjcdYZUxAE4+pISsnCwgLXr19/TyQzy7IQWnOuVuN2uz1WHj/XKPBnr07xR3c6eJbgTitgvxOz10/I0DjSouDaFD3JJ1br1IoOTiQoOja9yLSvSo5FcaKQw2N9nlmojt9Xa82rGz22ehFl22aQGDuAXpzhK00lVZybKHB9vszrm322uiGaBJ1B2bG4OlPBwrQt23u7FIFz89NMTRu7Zq01U+WQbpxyMEwMYkhpiq5Fo+RiW4Jm38KTFl5uMR+kOVveluz2YiOFlCdRzzbzrN1+xDAuUnLsYxNhI58UstMNKfsOM7ZLmBi0Uq1gbvNMZahc/kkIgdQSx7HRRx5uz/O4cuUqrdYBt9fW2Nvb4/z58xQKx223wQjsPjdfgVSzJgP6UYajNLMVj4228UYqeZIkNaTWVJvFteRIhonxPbIcIwk0UXQI8vbaZNFid3iy9sQYXKFMa0gICKIE4gTHkbiOi1PyeKcr6IcBri2pFZ28ZZeRJAmWAyr1aPZinluqUfcdvn63i6WNIkaijEjviL8mtRnA28K0/Pb7MW83B0SxMmLBh3cVZIacnf8XJw2rTktOdm53HiXG90vrQw7dSJpnuuTyf782Q8mzcjsJcGyLl+60eXuvT7MXIRA4lqm6iggGKuOb+xqLAkLFJEnAnaam2Y+Zrfpcmy+P77UgMXOs2Yr/nsEPYDhlE36dKDYu0AXHoNfUSBPrIWE0GCHVktmaaW33g5B+EONIm6IjORgmFM8g5FqwbUrOewNCnEVZ/INW3hOMkSzRSaGUYn9/n83NTQ4ODpicnOSpp56i0Wi8ry/FypUfXMtipVbjdqczftgvTZWIU8VWK2SlWqDq2MzWMnxLUnBt5us+V6ZLnJs0i2bRszk/VeDGdp8gyXBti2GcUi3YXLhnONoJUm4fDPFti+vzFW7tdejHae6DJCi5xgnWdyyeX6qy0PcIQrNg+SQEzQ1ebrWoVMqsrJyjVqsdGxILIVidKplEZxk7cdcyx3Zsi8mibRbrTNEeJGhpFqG5srHb2OlFOPc8cCNF9CzJMeuYVt2dVsBmJ+TGdp9BrJipWuNFptmP2B/ElByBynKbeCGxLGkWHH28XTWKiYkG1WqNjY11XnvtNebm5lhcXETKw52j1JKLUyVqvsOVXkRnmFL0LIq25P/9h+uG4Cok2EYtwMpM9RCmmZG5UYo0kdieub8KjoUGqr5HO+xzEkDRllD1DFJzGKX4tuJi1WFhssZWP6Xm25yfKnGrOeBgEAOa6bKDLSxsWzAMU3Qa0O906Q09rsyUqJdco7iRKGOnkV8Tm0MiNhjuHGi2ezFFR1IpOGy107yy0ojs/usoMPy3ez/LScnJtUylP/InPHosjYHIC8B3LdpBTNErYEuDl//k+QYXp0r8k/92A5VCwZHEmUGQttIYxzL+UiuNAlo7TDlgZ33u7EfEScz1+XJOKle59qOmNYzeM/hhrxexsR/SHsZ4tmS5UWSxXkCiESMX4Icco+TZ+BKGucBspWBRcEs4tkNJJuxub7FdTlmorZ56jnXPZ6FSeU+zMviglffHHifBxcMwHFdHAAsLC1y7du09VUdBkrE/MIKukyVD0pNSjglsvm2zUq2y1umgMVYVz89VWa749CODMpssOeNZyUmxOlmk6FhsdkPCWLFQL7NU86jeYxkdJhlZpnEsge9YrNQ82kONU/JJtWKlURgbkNlSMFtw2R802d3boxXHYyPCkyzKR7Fc99nPfaQqnk2W6xBemPSZrfoMkoy9Xky1AGmmGGibCw2HmapLcd9iEKXUj5z3MEoo29aY3NiPUl5a7xjF8/w1Gs27zQFzFc/MJDJjpFbzHRzHOfkBzkzv/t48YFkWKyvnmJqa4vbt27z8yiusnjtHY6IBuS/Wve09MMZ8nmVRdG0SpRFKG8CJFvTjjCQFITVCSDxbkCWa7SSm6Ng4lqkOL0wVuNuOTFWCWZAtYRZvqVIaLhTLDhenatTLPs1eRMHRPL1QpeTaKG2UAXb6MWkGBd9w0jIX3EIVS6fsdQa8u7aJX6kZodf80tjysBh1pWSq5JAoRZQowlQz4QmKnpXPtxyCJEMkRt5o1JYc8aQsIYzgLyckLcWx5DQqvnwbXNeG+GR0YjdI+MPbbTy3y8dW6lybr4LWfPnNJu1ekr+XAizjvZQZ80TXkqAFFd9iuuxhOxWa8T773YCv3ljD8ssIaWNJQZYpLk2X3hP4Ya8X8tJalzhVlFybbpjy0t0Owzjj6ghwofLke8qhJ0suM0VoS4d2qNChxpKScsHh0nQdX2rSoM03vvENzq2sMDU1dSzRCwGzxTJTxfur/UeJh6HynoRN0AeJ6UhUKhWazSZZlnFwcMDW1hb7+/s0Gg2uXr1Ko9F4z9bJt/aHvLzepZN7rdQKDs8vVWnY1jEeU9FxWK5W2eh2jZimEEyWPSbPqJIkhWCu5jNXOx2F41qSkmcxSDL6UYotBCVLYNsWYQYLNR/PlgTDgL3tXfab+/i+z+zsLJONBvIMOyjLEqxOFnMdO4WXS7NMlw258cNLNTY7Ift9s6tUg5DJso1nS1YbRV7b6hlEoSOJIkWWaS4vFMZitRvtkE7uwNqLUkquIeo2ezFoTdm3adgOjaJHseCd+t3pByQngGKxxFPXr9Pc2+PW2+/SLO1xbnX1gZuTRtGhUbLZ7ppKYjQTDBKBbUlsB8quTZQZKHSgM2QmiNMM33FItcJC8txClUGUkqqMNIpI0pTVusNHL0xzYW6KomOZ+WOSUXQt+mFGyTWPdNmzKXkW7tAgO8NUjRdcYVtMVUu4rstOd0DUbpKlFlZO0DaCpxBnGY4lqBUcZms+b2736EYpQZzmMw7NZMGm6lj0M2WI2fdkH9+RZBp8pejeL653DK2XaLPZKDrGLPBeMd0RD2u3n+A2+9jStBWLno1E8OqdLlKCpWAYKhQKS+bIQykQtsayzLNnWxKhoOi6ZEi6SYYdHOD6RQJs2kFKac1mLj4Z/JDmM0TXEsdbklpzey8gThVzVfMMVjAcwjsHQ5bqPiXPHmdwkVdOUaLY60eEqcK3BVO5o+5ySTFTLvHOQcggyoyyeNGh4Fhcm6twZXaJ/eY+a3fusLW9xerqKpVKFUsIlj/gMf3vEUopvvrVr3L16lX+4T/8h3zHd3wHly9fPia0+F6i2Y/5g7UOaM3yhDnWXv6zTyx644ppFGXXZaFcYaPTO+lwjyXqJYfZqk83TEmyjHaU0Q8yfBKuzZeoy5Abr28yHAxoNCa5eu0qpdLZsqPSmrWDIbf3jc6fJQVTJZdzk8VjxmZlz+bKTBlmzH/fudNFKwPwWG4UsC3B3YOAIFbUfYelRoGFI5qArWGSt780vg1FV9KPM0qezVKjyFTJZbcfs9Qo3Ke8flLoHOJ9khC6QDA7NctEdYK7d+7yyquvsLS4yNzc3H0zCMeSfPvlKdYOjLOsLY2xny1F/vnNYp9mir1eTJKaNqaQcHG6iGdZvL7VJYxjyDKi1PT4n1lo8Jc/tsKk744TQCknVbmW5JVNg74SmFbsQs2n2U+wpAEotIcJVd+h6FpUfBvPkVhSEqU+g90+oUpxbRvPtYy+nO9T9myuzVUIkozXN02VmOSWKEmi2EsUnm3h2JosNiAMS5r2ny0lczUfISTtQcQwjU+Alo+SU64mISFIU+L0fl+sUTUWJIpbe0McC3a7NlO+y/JEEa01cWr+N3qbXMcVR0KSam5u9dlsh8xWPHzXwkIwXfKQtiBKPe60BmRZyGTZZ7cX0g4F17oRq9PmvotTxe19I/OVZkYl5PxUiUbJRWWaQZDSGST32Z2XPYutTjq+P8eRQT9JeGm9y/4gHpO8G0WXZxerNDzF5StTXB+kbHdDolQzVXFZrBWYrXoIIZianqYxOcnmxgbf/OYbzDQafPuzzz1W5YfT0MX/x1VMn//85/ln/+yfsb29zfPPP8+//Jf/ko9//OOP9T2UUnzxi1/k3/7bf8uv/uqvUi6X+Zmf+Rn+8l/+y49NMXezEzKMU1YbhyX1bMXj1v6Qnb51n/IDQMX3mNOare6TkUiSQnB9voyUsN4K2VUJdgoXGpqpcIv+psXU3AyXL11+ZHLdVifije0+vm0xVfZIM2UeZK356Eod60GGclKSZSlCmeplseazWPFJMwONPdpSMXM5CJMUlRlOzUqjyFo7YLsT0x6mSClZnChw/p752mmh1eEudhRC57p3WuPYDhcuXGB6eopbt27TbDZZPX+eSvm4/P8z81X+rw/N8f95aZsgSSk6NhNFw/d6Z8/wlC7PltG6nzvoGtDETNGj3e+RJgk6hdUpj4JfwHNslutFrHusGUYxW/WptwK2uxETuQq71vDh5ToLdY/WIMmVFIRRtSg6vL1r1DCSVFMveGy3+wTRkAzFRKlEpCQTJQNpX28FOJbEEoo4Udi5qkMUZ2TKIElLrqYVJLhSUPRs0lQTJopLMwUWax5qo0trGBNn91amJjkhBVkGQawIHiK/lmqjrxhGKV+6ucuF6TI7vWjM+zvaOtQY0Ibv2HTChE6Q0slBA1dnyxRcw5G701FMT5Sp2xAOuoTDCEfA7YOQqWqRXpjyxlaXg6HhUNmWYLMTstePmSm6dANjbLnVDmmUnXH1CgYBK3N5seM3HLy52eegnzBX87CkIXnv9CJubHVRGuoFh6lq0bQsHxBSSpaWl7m4vMxgc4uvvfgi586d4+LFi++bHPsw8MOTiD+xiemXf/mX+dznPscv/MIv8IlPfIKf//mf59Of/jQ3b95kZmbmsb3Pz/3cz/GzP/uz/NAP/RA/8zM/w6/8yq/wV//qX31sxwejfWfnMvyDKEMIY07nWMI8pEqd6ANVL/gordnpvT/S74Oi6Np8aLHKjGtgyspNmKnB7NRFKtXqfUTUs4TWmvV2gIWglu8aLVsyU/Fo9mMOhvEDeRwj+wwN2JnR/UKI3HzQhDrCPZopO2x1IgaJolZwKFuCqaKi7rtcn6/QKLk0SjbWo6KqssPkJBFope+bj1QqVZ599hm2toyNwWRjkuWVZZwjys6fWG1gS8lrmz3KnkW94KAwtu5xZoQ3/Zy4XHIsanbKztYWfW1R8GxmakUmKx6OJZksugzDlJ1edN+8EKDoWTy3VOXt3UHOF4O5ms+lmdI4UR2NbpDw9u4QiZm5XJurUPJsdvtFmr0udtRlrl5ipTFB0XMIU8VGJzBt2cS4xUpye3c0mTLcMZlnBM+xiESGEIY7t1QvEiQZN3eg3Y+53zrT4NEzLQjPcstpELm0RidUbHejsbtr/utjobRp5zWKDlmmiZSi4tsUHYsgzvhmu0emNb4vCS0br9rAjkPKWY9X391gvxfST2CrHdAou1R9h3LBpmBbfP1WmzUx5NJsGc+WpJnilXz2WS8YMvowUUyXXWr3fHf9OKU5iJnwR/epgadPlFyag4hCxpna5mAcDGZLZZieodPpcOPGDb785S9z+fJllpaW3nNlc1or73H7143iT2xi+uf//J/zt/7W3+IHf/AHAfiFX/gFvvCFL/Dv//2/5yd+4ice2/v87b/9t/mRH/kRXNflv/7X//pEtPImSi6777bY6IQEsZHMrPgWri1pLJXZ5viupD1MaA5itIbJksNk0Wd/+HB+y6NEkiQ0m032dndRWjNTrdDvply+eHn8Gp0rKjzE4+9YKG0SsXcPCdaWApW3Wh4UAoFWCpkrEsjcL8jYOtwD9bYkCxMlIiW4fRCy3Y1ACGpFh6fmyqeSGM8UI0daTNvqYJBwMIzpBsZKouLbzFU8FhYWmJyc5Pbtk7lPzy1W8WyZK2woPEfwZ69O0Rom7PQi4jDEFxmkMQIfr9JgGCp0GhGniiTNUKnm9mCAJSS9yQeXEhNFl4+ec8YLdMl7sLhm2bOZKNrsDxJmKi6OJTk/WUAIuDY7z9MLPq2dDYbdNVZWVig4RV58+4CSK5ksmsW8HyYMEuOVFGeagmMxv+AziDL6uZDffM3nQ0s1GmWPVhDTGhrn1yRWJwHJEVobDbkjYuz3vS5v9x6d7UghUFqNeVcjmPkIiDGSmNJIEIqKZyqaKMuQUtANE9AGCHQwNFJT1+dKNLd6bCUZ251NPN8nFg5eJFk7GODbFZJYESbZWPkkVZqSZ9HbTXl5vUPBsSi6kmtzFa7PV+/rFhh7FMOlQxmHai2M+rvKVH7epz+AUggWKxVq3uFcuVar8fGPf5ydnR1u3rzJnTt3uHbtGpOTk6ce66Q4jcf0pOJPZGKK45ivf/3r/ORP/uT4Z1JKvuu7vosXX3zxsb7XUe+lSqXyRFxsPVvQDlI6QcxM2UOhebcZMF/zmK74bHNYNd3c6fPqZp9BZB7sgmNxfd4stK0gel/nobVmMBiwu7tL6+CAUrnM0tIS9Yk6QW9I/4SZltZg6dz5+gxhSUHFs9npR1SO9NKNArLxLnpQCCkMUivv86hMoVGkBv6W21IcgXoDl2cqLNQLdIMUme+IbcvI2tgWj14t5SGVRKMZpimvbna5vR+w2Q6IUkWt4DJVdpksOTy7WGO67HHl6hXarVbOfWpy/vwqhUIRxzKKEauTRaLUaAC6UrO5vUOh32S5DtemamyHFokWeLZgmMbYWjBf8qj5LmhIbcXdthmqnxZCCMr+wx9rKQVXZsq8vNFlsx1iW5JUKaYrHs8vVmmUPWbrFdrtFmu3byOlw0zBZbMXoz1BP0qJlJmdVH2PONXsDxJKrqlCJIJGyeXPXJ7Edyze3OmPUXy+E6OUYnhijj1MTkIahF6UHgFBZNwnwioFSKGxhDQVvtDjKns0b5LCHMO1BL3QWMnEqSJIMuoFm8Vagd1eTBRnVAoOkc642wp4pwWOb3N5ypDv273YuDxnHp1BgiUESd5qHsQp/TBlvR3i5J5QZc9GCE0/zLi/7jaQ8FrR4WBg+FQ6M1SI9jCh5ErzvJyyFrmWxUq1hn9Cq00IwdzcHDMzM6ytrfGNb3yDiYkJrl27Rql09vb2aa28J8Fhgj+hiWmEjLvXF2l2dpYbN248sfc9jcf0fmK3F7NQ81iqe+wPjFr1swsVlNa082Z6lmW0I81L6z1c26DZADpBwivrXb7z6hQ1HzrhoycnlRln3N2dHaIoYmpqiutPP02hUDDzE3UoYHri36sHgwJOiuWGT3MEE/dtkkzRCVKWGkZm6aQYSfoopdFKkeWJGnIDQ9skpZPIjiXXpuTaaDTbnYjbB0MGUYZnS1YaBZYnzibYCbmoaqbHwqg3N/psd0314js20xWLztBo1AWJ4u29PpOlCaQQR7hPG0e4T0tIKSl7NjIbsr2+zf5+k3K5zPNXVpmYqKMxQqTrrYAwVQYgoUElmijKQMAgNog7+z2oEDwoGmWXj52rs9uLGCYZJcdipupR8mwj8SMkjYkG5WKVd9c2OGfvEDo+g9yvq1Fw8F2LpbpBgf7RnTZhmlGxbGarHhenTRvxD+90jMqFUjT7MXbOJbsfAznyRTHJycKIBYtRyZOdrAsupUAjcBxJqszzNNJKlFKPKG+kqSKKM4JE4UhFpiTD2IBCagXHoBgtSZjbug+ThEhJdKp4pxkzXSlSK6e0OyHRIGKp5KKkQ2sY41iSKO3RHET0ghRLGAHh+ZrPMM5Ybwfcag740HL9+LkLY3ExiFI2OyGuLYhjhe9bnG/47A8fvLEqOQ7L1Zp5Pk4JKSXnz59nYWGBt99+m9/7vd9jeXmZixcvngpqGMXDWnlPIv5EJqY/rnjc6uKj6IWm1zxXNRp0YJBbawdDolRjWRZZlrHTNdDfueohSKJWcOgECRvtkI+u1FBa04vu79CfFEEQsLe7S3N/H891mZ6ZYbLRwMp3P1Lni7AwduT6BBDGKPQjJKeZis9ziwYi3w+N3fmlmRIXpoonJgipQRn5abIsJc3MHM6SEmlZWGaQ8dB512Y75JX1HggjVBsmGa9sdImSswl2WnqUnM059uOM5iCmZFnsxhFlz8KWkrJv0Q4SpkoO7WFKL0qp+SbhGu6T4ZTcunWLZvMlpqam6PX6DAb9XLbqGYpHuCUCY9mxNGFmiu/sDCE1lUE3TEEa/USEac89zij79oMrLKXZPAh452BAPypQnFpkiSbrnSGO6zJT9WgUXRZz88Rn5g0ApOBaZLm00Fu7fZJUMV/zeWO7S6rJze0yhslRdQiBOGbWJbAh12pUiBROzEoYRYrpskvBlez1IIwVti0o2BbVgs2lqSITJZ8/uttmsx3g5tL6CqPIEccaKTQXp43Q8ju7A7JMU3Zt0syYIXbDmH6cMF30KPg+YZLw7sYOwvEpOC6OZaDxvSClNUyYrXpUfcf4vHk2ez2zUTspZioeHz03wWYnpBemlOoGUekS0ZInf9+ThQJzpfIjVSue5/H000+zsrLCjRs3+J3f+R0uXrzIysrKqVSKD9TF85iamsKyLHZ2do79fGdnh7m5uSf2vqOKSSn1WHuqE0WHOy1jqT6CLWf5QL3oWrRz9Yck0ycv3FISpwohBIu1CnfbXQYPIB8qpWi32+zt7tLv95mYmODKlSuUSqXDm1jnSUkzbhMIKU+01zgaj5Kc5ms+MxWPIDHAjxNJwRqE0qRZZsQ7PY9+v8/GxgYry8s4R104tRFrNcnp/hPItOL2foCUhpgIh5prd1oBy43CA11HTbXGfZ8/VZosg4JrWoyjToyVy8pkI3HSE47puA71ep2trS02N7coFApcv/70qS0UgcBBMFlw85aXZGnCR2uItWKQKqbK710l+lFCathpR7y63kNIqBUsUmWRTk1jF4bs7repqy5Fq8Hdg2HeyjMV8vJEAdeW3Nzus9kNuTxdJlGKXpjh2RBHCUmSjXlKOm/OHUXSlR2JZYMtJI60EQVjB6O0Hs+PIFfal4K7rWAMRa+XbXzLYqlRYLrs86cuTHB+qkTFt/jNG3tkmWYQZzk0O8PSxk8syxQFzx4LxFYtyU4sUHaKUpCFip04wrYEF6dL/OmLdV5f28HJekRZhUEoxyAnz5aU8oQfpcqI7J5CWagXnfu6Ce328L5WtBCwUK68Z0FWMBvwj370ozSbTW7cuMHdu3e5evUq09PTJya60yqm/6Naea7r8sILL/DFL36R7/3e7wUOYd2f/exnn9j7VipmxzcYDKhWHwzNfNRYaRS4tT/kbitgMpd/aQ4SZise8zWP7Vz9oVHyUECSqXECS5XRVJvJLSuEECzVq9w56BAc8cKJ45i93V32mk2kEEzPzHDh4sXjizsgtDZyMPeco1FS1g+drz1KcrLGvJ2TjqPQiRH/HFmaT0xM8Mwzz7B2e41XX3uV1dVVo7IwCmUU2TNxv9ZYlGiGcXoMogtmBrLdM4itkxKTwKC7TqoVy65FyZMEeXutHSTUyg5BovBtSRArZqreMc7KYDBgZ2fHtOsqFS5evEC5XObu3XW++cY3H8h9EuRKCBqmSg6XZkq80xzQDcys0bMlV2aLTJUfn2X2STGGxitYbwdkWjNb9Axi0gbH8lEKLiwXWd9t8drb26TCQQuLKIO5iselvIVX9mxuHQx5c6dH1RXstHoEYUyUmbYbEoaxIuO4L1XZt3hqpkSUaK5Ml6kXHPyCxZff2me3H42l9i0pORjEhsDrWKTKWI+kmcYuSOJE51qJZqNS8Z2cPKyZrXn0woxOkJBlyth9DFLq2mjUhUnKZgxhBjo1yhUIQZAqrIzczFGyMDtD3VVsbW8zTIZcbNSJU02UKaNIohWZ1lR8m6X6o20qtNZIpAEgoXGkZLlaeyy26UIIpqenmZyc5O7du7z66qtUq1WuXbs2XgdH5/CgxDRaL55E/IlMTACf+9zn+IEf+AE++tGP8vGPf5yf//mfZzAYjFF6TyKeVGKaLLl86vwEr2/1aPYTpBRcnCrw7EKVgmON9fIW6z6reRIrubnsTpyxMuGzPHF4U0shWJ6ocvugTfOgxe7eHu12m2q1yurqKrVa7cTkYlp3J8ugjNjtWinEQ6rFR0lOR0Mps/LqTBkirZBYUmDZFjJfqIuFIteuXaPZbPLuu7doVpucO7eKl/fCtTLaZfe29RxLYFuCJMuO2WLEqc7VzR9wPY6Y9t0btiW5MFXi1Y1ergitubMXIG2Yq3pUCjZXZkqgNQetFtvb2+N23TPPPHNM+PU07pPIodLjZ1wILk0VmS67Y+h3vehQ920EkpPwbI8jjiZHjaYbGBUGMGrpnWFKjFF4WJ4o8NqWQ0+5REmKUsb6IkpTuA3ffnESyxJEUcztdsCkkxFJG+H4FH0LO8noRMlYmQGM5FLFd3hmvmSQq45koT5StddcnCzQHibMVk0bca0ZsN83yiCjNpqZERlNxJWGj21J7rSGNEo1FuoFfFuOZ58FW9IVZlOyWPeYrnjMV1xubPVIMsgyY1om8wdGyxGfDgZRwu39IWXfZr5W4uL5C7Q7bbZ39ygLC98u5XbnphW90iiwWH+0KifLMixpoTNN2XNYrFVxHtDae68hpeTcuXPj+dOLL77IwsICly9fxvMOyf8ftPLy+P7v/3729vb4qZ/6Kba3t/nQhz7Eb/zGb9wHiHic4TjOuJ30uGO+5jNb9Yycf85jGiWPkV6eY0k+eb7OTMXlTitAa3h6vsz5qdKxVliSJGxvb7N9d52N3oCJqSmefeYZvAfp1mk99ix6EMJnJO0/ss14WOhMI62zQckPuUcKSwsExmZCWnKckI7GaDdXr9dZW1vj1VdeYWl5mdmZGXPNcrLi0fd2LMlizQjY2pak4FjEqaI5jFieKNzDxM+vxxlc3JfqPo4tWW8F1Hwj1VP1LeYnC0z4kn5rj9s3d0AI5mZnuXLlygMf4mPcpzfeYGpqipXFFWzrhNcLkdvCH98dm+v+6JuCh4W5HofJUWDQfbvdiDiL+eZWl4PAOBtjCaI0I06MF5IouPTChH6YEMeKteaAssyQaUgwUDSKDtVShUjBQT9Gas1TsxW+udNFkFLO+TuebVH1bWZKPuudkHrZGlutgMCVEtcy/mP9MKUTphRcwwfc78d5p8HCtgz6bqcXMVk0KupJppmvejy9UOXLbzU5GESAQOUw96JrUXIt7rYDImVU0+P0eF0u1GErOUgU+4OYRtlhpxcxUXQoVqrU8LjgtRFhG0/UmKg3mKsXWG0UKbiPllSUUggpqBd8FqqVJ9IyG4XjODz11FOsrKxw8+ZNvvzlL3Px4sXx6OSDVt6R+OxnP/tEW3f3hhDiRCHXxxUyX2zujRH4AUxL4vp8hevzlfte1+v1WF9fZ2dnh0qlwsUL5/no5CR32z2SBwEXctTdw/bYowRxGgDiWAiBzjTCEidWYKPqKMuPJwEb6xDMcIZwHIdLly7Rbre5fdtUGhcunKdYKOZtPUF2pHI6P1UkylUm2sMEW0oWagWemqsc8VTKla3PWnQIwWzFM+6/OeF3MBiwvb3Fm+19ytUKq6ur1Ccm7oMxn3w4Y5My2Zhk7dYtXn7p5RMFOE+Lsa7f41gPtD4C+jiMMDXw/vV2wNr+kERpKp5NrE21++7egHaQMlFyiGJFybMRQtANYpI4Zac9xPNdajWfUp7QsyRjquISppoUzfmpMo2iQ5AqDgYRWaoJo4zNToSfK8m3hsb+JEpNxTbpG6NDyzKk1b2+wJGCvV6ElALfMVV41bcp2hbNQcRUxUGgcWzJn702TZopbu70cW3J1dkSUWoURIqe5M5BaqxdLJuU9P4WbybQFiQKNtoB/7eLk3iOZD/nHU5VPJ5fXiUIAm7eXqe7vcZqaZGy9+gdGK0008UCi7XH1715WJRKJT7ykY+wv7/PjRs3uHPnDvBkZIdOiz/RiemPI55kYnpQjFp5J0WWZezu7rKxscFgMGB2dpYXXnjhWB94eaLK2kHHKCUcCdOqOhkscF+IUcV0xsQ0+psxKdD86Kgyg3mJwJYSqeV7FsCt1+s8+9xzrK8bC4r5uXkWFhexkMcqJ8MZqnCuUSBIFK5lBC+PGv0da5k9QmitODgw7brhcMD01DTPXX8Gr3yycrNG535Q4j6dPgEUHI+rl6/Sare4ffs2u3t7Y+7Tmc4nI69Y30dbbwQouecrbwcJr20Y7bZOkLA/SPBtSeZoagWHyaLLdjcgSY2SSZYpbDKyOAEhkbZNL9PstWOqfsZ0tcRczTgnJ0qx0Q4puBZLRYf5WsFcLaXZ6cS8ttnFkoYucfcg5KX1Do2iixQQZYpMw91mQKXo0Cg6tAYxYZJR9W2EMBYRviOZKBmb9UGUMlGwAW3MDR2LP/f0LJdmSmx1jK1FxXdYrBvR4vVmgI3AcySu8Vc8lpwsARYCzzJgoV6Y8G2X5hhEae4XpXllo8PBIMGuzTLsD/jSjS3Wt/f4yFMXzjwisKVktuiT3O8N/C2JyclJ/tSf+lO8/fbbvPPOO3zta1/j2rVr1Gq1b8n7f5CYjoQQ4olBxk+Lo9YXoxhZtW9ubuJ5Hov50PykNpFn26xM1FhrdQyyTOtcSgfOlJQ4BCA8iMt0yl+axV7oMfdodCwpJLa0cpb+Ix72nrCk5NzKCpOTk9x69132Dw44f/48tWr1WHISCKq+Q/WeruaIn/SokSYJO7u77O7uIIRkbnaWq1evjr8HY91wvCLd60e82xzSDQ0Bc77mc2GqhGfL43Oth3CfHhbvp6034q/dm6Q1huTdDhIWaj57vZh6MTFKD7GB/reHifHssqA/DFBK47s2ru9DZlQLJssuaZpy0AvZbXcpuVB0S0aRvORiCcEwMe3dODEW6Wv7Q9JUc2mxRMm1qPgWO72QzU4PrTXTZeNWGyWafpCipKZWtDkYpAzjDJETa+sFhyQzSXO24nNltkyYZGy1B+zkPKq5WoHVyRJCQMGxsSTsdiN8y7T0otR8Dkvcr5gupaDqWtRLDgdBghCMIfcv3W3TGqYs1H2j9F/12S2XaA97vPr6G0xPTnDu3LlTdTh922a5XuNOt032HjdzYMAJW52Iu60hUWoAVCuNIsUzthSFEExNTbG+vs7ExARf/epXmZub48qVK8fsbv6Pa+X9ccSj2qs/jhi18rTWY6v2VqvF9PQ0zz77LPV6/aFfvu/YLNer3G11QD9Cq+pISCHvX6lOCZ0nolG7TuQkWMu2EEgzNH7MqJ1yqcTTzzzNzvYOb968SWNyknMrKziefeLeUnCIMnuU6Pf77OzscHCwT6VS5fzqeer1+n3tNp0v8OTJqdmPeeluhyQzSKw007y502cYp7ywNHHi5biX+7TffHncHnxYvJe23hgEc8LvumFKa5DQKBprEs8WhEmWb3jM9dzvDegFMTM+zBZ9NnJxO9eykFIxVTZIxdlyhTd3Bxz0hry702YwDJiuV1iZLBHkhN4bG316ccogzNjuRVR9m9YgZrdnlNe7YUp3mIDQhHHGIHZZnigwU3Rp9mMWqz6XpyW39od08mQ6U/GIM6Pf95GVGr5j8/J6h412iG8bRY+tdsjKVInnl2oIodluxbyx1aMXpji2hSU1cZKQZIeuwZYA3zaK6RemS3SGMUX7cJEPk4xmP6ZWtI/RPibLHnsaLi7P029u89JLL7GwsJAbTx5PPFXfY7FWRQrxvu0mvrnV44/udkhz88M3d/ssNgd8+6WpM6mDgOEwOY7DlStXWF5e5ubNm/zO7/wOq6urrK6uPjGpog8S0z1RLpe/5RUTQKvVYnNzEzBmhE899dQjq5sXXYelWpX1g+57OgfDZXr4Cq7z4fCouhpVR5a0wDLDUK30Y09Ko5BCMj8/z0SjMTbwO3fuHJPTk8fmXSMo+FnPQmvF/v4BOzs7BMPhiei6k/+OsSPrejsgyhRzlXxH6YBrC+7sBRSkRaPoMlE82eyxWCzy9PXr7O7t8fY771CrVTl3bvWh7Hw9Ep19WHLSDwd9aG0qhNF66dgyN/tT9IOQNDAWFZbj8snrc3x4uc4f3GnzzZ0uiYYgyij7NrNln6UJn2GaUXAlYZwxYYW44QFJAJVCmYtTJXbbRsmkVjTKHfWiw1Y3JFOGa2Ts5hVKC8I0I2iHJKniz1yeIi0aqZ+VssfHVutstiM22yGtYcqFqSJLjQLnJwtstkO22iHzVQ9LmsQUp4q7+wPmKy5aCV6+2zE8wXqBdpgwjDM8K2dWSUmaGdv3UVt2s23U1q9Ol4/wr07+AkZSRI7jcunyJaY6M7x08xZfe3uH+bk5LixMMVP1mauUmC4f8tzeD5+yPUx4bbNLwZE0cph6pjS394e8udvnIyv1Mx3naHIsFAp86EMfotVqcePGDdbX13nmmWdYXFx8T+d4WnyQmO6JJyVLdG9orWm322xsbLC7u4vneVy5coXJycn3PIsBKPku8xMVNluP7uUkT5ElAiNtNK6OjigzCHEInjBAC/1+O3dnCt/zuHrlCvsHB6ytrdHc2+P8xfM4vmdamdlJ6mT3R5LE7Ozssru7i5SSubk5po60684SWhun2vYgoXQs6Wha3YR394YMwox60UjfXJutsHASr0UIZmZmaExMsHbnDq+8/DKLSydzn47FQ5KT4Sc9HIlY9mwqvkUnSJksOWRJjEtMO0zJhATHouy5LNSMa2+j5PLpp2b4jitTbHQD/nCtg+9I5moeAsF8xac7TBGu4NLiPMFgyMb2PsvVHnFpkVrB4cpsGQ3cag5pDxO01nTDlDDXsksVuUCrsTzf7sW8utmh4DrM1zwavmO8rKZsZiouvSjlucUqjbJJ6PuDxCTY/LkSCFzblLj7nZB2YMRfK76FJT2epso7e33uhgmTvmBltk6zn9DsR7nySgrYTOXOxSNane9Ipsouaweh0QvMq6bWIKFasHMPLs3trqLrzZBkA77xzhZv3G3yXc9d5unZ6eNfaZadSTLopNgfxPSjjNXJQ4i6JU2b887BkA8t1cZI3NPipKptYmKCT37yk2xubp7qYP1+4oPEdE886YopTVO2t7fZ2NggiiLm5+dZXFw0PfTp6Ycf4AxRLXgopdnuPNrnEPJ+WaJ7q6PDhHQ/1Hs0PxGAst73WOls5ywEU5OT1Gs17ty9w8vfeJnllWVmZ2dPX8i5v1134fzJ7bpRHAxiNrshgzCl6tvM1wvHrN/RgpJt0QxiKr65Hq1BykYrwJaC+ZpHreDQChK+ud2jeoockO04XLx4ke709BiReH71POXK/WjNcWTkKMmTQDBnK2BtKbk4VeArb22ztt7hYJAxSCXT1SL1ootnW7i2EXENjwjKepbk4mSJKFW8uTMgiBWFXIS0VrRxbIlWgnq5zPUPN3CiDq+98y4HusxseRbbspiv+Qbi348ZJhlRbMjltiVxECQ5fy7LFGsHAdfnHWYqI34bCAkVz6EfZseAQJYU9wGDLG0ITFoL+pHxqlpvhcSZ4UBNVTwGQciz0zaN6TKIAYsTPgeDhFQpnl+qk+Xaf7NVb3yvX5gq0wvTXBhXGCFX1/g+2ZZgvRVy5yBkquLi1gtcXphkcNDjd7/xFoW4y596/tq4U/J+KiZzC+sxaXkUCo0U8qwA0AfKEQkhmJ+f/z8TLv7HEU8qMY2kdra3tykWi6ysrDAzM4NlWdy+ffuxV2n1ko/Sit3u8Mx/I3NrCuA+IVUpBVJa47bd0RAA97TMZA4K+FaFbdtcOH+B6YlJ3n3nFvu7TVYvXrhPAui+dt30NM8+8yz+Q1yKtzohr252iVOFa0t2ejEbnYgPLdWYKh/uahfrPnv9iN4goeLZNPsRnShhsWa4VEIIGkWXzXZIcxA/tNdfrR5yn964YbhPy8srD67m7gFEjOZJAGGasduN6EUpBcdipuwde/80TdjZ2WVnZ4cZJDOLDbZDi/bdDgJBmCrCVJFmRmJnpPs4vrYKLk+WSJViqxPRCRNcW/L8Uo0r02WkMu0wI81TxSnV+M2X13jz3VvMT09Rr9e4OF0iU1Av2LzTHEKUS0ZJgYPOFcLluDrJjlb4CiJlzs21D2++mYrHnYOAYWws6IUWdIcJrm0xXfV4a2/A3VZI1bepFywypWkOUlKlibUgzYz9S8UzthYTBZe5qsf+IGYQ5+oruWJGreDw0dUJdroR/TDFdyQzFZ9qwVznZj/EkmYe59k2U6Uyst5AFGrsdg/G+nXnzp17XzOmmbLR6tvvx0znqjFJpugFKU+tnp0T9bBzeFIw8g8S0z3xOOHiSqkx1LvX6zE7O8uHP/zh+yCjp8HF3080ykUypdnvB2d6vchFVJPEqA3cJ6R6Qhyi3e65QXWuP/ctSk6j5Fit1Hj2uWfZ2tzkjddfZ2ZujqWlJbIsHbfrLMtidnaW6WvXzvTgp0rx9t4ArWHuCNxvpxvxzt6AyZIzfkAXaz5xpLi9P2S7a/hUNd9hpVE8dg2FNFp8Z/psI+5T7vv08sunc59GM6ejoI9+mPLSRoeDQYwUBupccoc8u1ilYmdsb2/TbDapVCpcuJBXjghe2ehyc3dgmrP56Y4W/U6QEiQZUZLhORYFx4jcPjdf49ykqag8S1D//7d35uFtlWfevo82y5ssy9bmRYudxEkcCHyUJZSytBRK6d6h02kZIKXQAqVQlpIMLe2001KasK8BOizTYYaBGVpKCzOUlrWUsockzmZbi2VJliVbtmXt53x/yFLseJN3h5z7urguYh/pvJLPOb/3fd7n+T0l6glXa3U1lXxktZ1d3jCuYARVqJ+yqmrWWCpZYSrjN+8FeKU9TU7/RhIsRnwXK0pyFj/RRAalkKa8REUyI9IXS9No1KIbJbimSg3NxjI6e4eJDuWuba1aQYupHFOFBkHIPbSV+f1RJFSCQLlGQSItMZRMjxTUJtGqlZh1uQd9Mi0WzHsLf6usRJlahaNm6uuqsqSEqhG/u96hFL6BDJoaM43VVva73XR1daFUKmfVPwlyWYJHN1bxlrufjlAs58AuSThqylhhmt7QOM9cEzBmiyxMB6HT6caZx86UeDxeSPVWqVTU19dz5JFHjvOtyzNRuvh8YdSVkxUl+qdoNJgP1wkKBYODQ+h0VaimcGaA3GNCUXjwTbLpOzKLFOeeLT4lOXE88G+lQklDQyOGmhr2d+zn7WAAScr9bZuamtBXVRVdzAq5h/pgIouhfOztUlWqpj+RJpbK5tpaSIAIzbXl1FVpiaWzePqHcYWHKR01g8+MTEIqZugUXjKypxbp68PtdhHqDeFwjK99EqDgxp3Xg/beGJFYGqtOOyKiEu5QP39+14+9JIHJOHGiRyojolQoaKgqId/jUa0Q8PTFCUQTvNYeIZnJmZbW6UtYZaxAhYIqjYrKEgklikn3LQVBYLWlIpfw0F9FTziCOBSkWp+hWlvJVz9SR08sRWcolisEVihQj4THBEGgoboUqyThicTxRePERpzsk0mRYH8Ks15TCDWtMVdgLSsptJkxlKvRlaqRJIkKrRpLVQnxtEj/cAYFEmXKLDWqFE01eiqrShlK5oxc6/Ra1EqB4EAy1yyyavwei5CVEJQT+y+aKrVEhwW0qhIEQcDdO0xbYJChZAaLroRdEbDWrKBeG8fbsQ+v10tNTc2M+iflWWGqoLpMQ3c0TjqbSyxp0JeOWU1Ox3TO4vKKaZGY7YpJkiQikQhdXV1EIpGR9gatVFdXT/vHG+38sBBY9BWIksTAQY0GR4frBEGgvq4Ol8tFPB6nuamJUtXE4a28p1pRmQUiKBWQFfIe0vOLYoK9E1ESCfeGCQaDJOIJKnSVxGJDqFQqKsrLZyRKMFLjJYx4uo26p6UR+yaFkNuzGF3MXDqygigvURJLiXQPJqjQqJAkiKUy1OtLx4QAZzAYDAYDVVVVhYLj0bVPCoBRK1iFEoYzIqGhFFUjhab9/VH6+/py3XG1lThbVmDWT5x5WKlVUaVV0p/IUqpWoBCEEZdvGEhlUCkEKstzxrb7e2IIwBqLDkkcaSOimPoiUSkVNFSX0lBdCk4DyUQSt9vNe++/T2NDI18+ysKv/9pFeDiDSpH301NRVaLi5X1h/p+tiiZDGXt6hkirJKrL1ERiaXqH+llpKWelpRylpEASQV+uQV8+9jsXBIHa8lzqeSotEo8Pk0wkSKrBqNexvqkOk07LuvpKOnrj9A6liKezmHQ5s9qq0slCqiNp/KN+pFYqOd5hpkw1xN6eIRJpkTb/AGqlgqMaq2gyloMErsgw1ioDFRUVlJSU8Nprr2Gz2WiewJR5OmoqNNTM5jrLf4xsdsbZwfOBLEwHMdOsvFQqhd/vx+fzIYoidXV1tLS0zChbZaFCeaOxjojT4HBibO3RSLhOqVJSXV2Nrqoq5za84wPq6xuwWi1jVk0CAmSkGS2BpFGu4PMpTgengidTSXqCPfSEelApVbnsutpalEoFiWyq8MCz220Ya41FC5ROq6K6TE1oKIm5ogRhpBC5L57GXq2lQq0aEaXxlCqV/L86He7oMIGBFApBwFFbSWN12bQN3qZCqVRit9sxGo2F2ien3UF1VTVj/jhZCUGSyGQyDPYP4o8NoFarMdTUUF5RQWgoXejPNRHVZWrq9KVkRInBRAZJyj3sBpNZ6qtKC+7xFSW5z+LrT9JkyFI6Ev5RMLNwbol2bDfgeEZgtbGSjKBkKJUhkcqZyA4kM/gHU3RFE5SPtJg4skGHauRaHU5lcfXGqK/UUlE69ZK9TCnh8ocZHE5SXaqkXF/JcEZAUaKlojS36ipXK1lfX0liZNlYqlYx7Z9vlDjlSznUSiXHOdU0VJfynjdKz2CCNZZKDBWaXBafAFXaXOacQRSx2Wy0tLTQ1tbGK6+8wqpVq6ivr180i6BMJjOmd9hoFspZHGRhGkcxzg+SJDEwMEBXVxehUAidTseKFSuora2dVar3Qoby8kiShKmylGQyxXAqXUhiODhcp1QocNjt1BgMdHR2EgmHcTY1UV5eNjLznJkoFc4v5pyZ58PfTZCAkdWJJEkMDQ0RCASI9EXQV+lZ0bwCnU435ubVKktYtXIVkb7ImCy36ZIeICfeLZYKUj4R/2CSfNMQY0UJK2orJo7ZjKJco6LVoqPFfCCzcb7I1z71Bnto39eOrkqXcxbQ5Ga5g0ND+P1++rv7iCnLWFFfR3lpKSAQjqXQlSrRTzbrB2oq1DhqynFHhjFX5sJP0Xgafakq5x84Cq1aQd9QmmQyS2nZSJhSnLk4AZRXVlFhbWZfh5/93b1Y9WU01BrwjTTTUwgC1WVqLJUaOnvjxDMifbEMxpHVQblaSXQoTTSWRqdVTXjdDQ0N4e/uZldXPxVqLbVWA0kxV6tkq9GQBUKDKcpry1AocveQRpE3PJaQJGH6uU0WDBWlWHQHmvqplQrsNWVkJYneWPKAKI0gSlKhcadSqaSyspJjjz2WYDDInj178Hg8rFmzhuoiCrDnylRt1UEO5S0aU62YstlsIdU7Ho9jtVo59thjZxX/Hc1ChfLEvDPDyHsLgoDNqKe7b4hUduqnaWVlJUccsQ5fl49dO3dSZ7ZSX1eHYg62+7Ntl1F4PaAc2dfKiiKRcIRAIEAymcRoNLL+yPVTrlQFUcIwYgGUXxXW1dVTV2edNrVcX6rmWHs1vUNJUhmJUpUCY7kaTZEbw1I2J/pz8rabgJyzhYDJaKa62oDH7eH999/HUG0gkUgQT8QxGU2cfsxadkdShIdTDGdSpEWJMo2SlcaKKRvYKQUFrXUVGMpV+KNJspKEo6YUd1+cTFYERj6/JJFMimgVCrQHW97MUJyyosiO7gE8kThVVXrqUio8oSieSDfaUi2iQo0g5LoUl5eocvtOWYneoSTGipw3oiTmaukUQi4tvHDdSRJ9fX34/SOeh0YTZpuD/lCCTFZCyubaP4pSLoMwkRm5L0f2qoSRHkSSlB2x3lJOKk4CAmZ9BdXlE09+TBUlVGnV9A6mMOlGZc4lMqy1VtIbOZAuLggCFosF40j5wFtvvYXJZGLVqlWUFjG5mi1L0SQQZGEaR2VlJbFYbEzDvFgshs/nw+/PdSKtr6/HbDbPW4+S+Q7lDSXStIeGcIVz2Xg2g5aVpkoqSzUoFApsRjXecJRkOjPl+ygEBbYGG7V6A+3tHfRFIjidTWMMZGdKTpxmZz6qECGRHAnX9fSgUquwmC2FjsfTn1xAyIJKqcThcIxYAHUQiYSnrxGCkY6ypQVxnDGiNG7fYS4oEEb2k3IICGhLtSgVSsKRMCqVilUrVxWMN8vLMgSHkkSTGco0SoyVJWPrsCZBpVDQWF1GY/WBkI5KKdDmH0QCStUKkkmRoWSW1eaKUa0qRjEDcQoPpfFFE5gqS1ArFWjrqtBqVHzg6yc6kEApJLFUl2EYEaFSjZJEOksik0UUQSFKRIbTVGiVGMpzny+bFumNhPAF/EiimPN8a8m1KNm/uwd/NIFVp8VQriGVFekeSKBRKjiq4SDT0vzDWMqZwkpSBkGhGFcbpFQoqDfoKC+ZfH+nQqviaJueN119dIRi5CJ5Ak215awwVhBsGy8KSqWS5uZm6uvr2bt3L6+++ipOpxOn07kg2XOZTEbOylsO5FdMyWQSn89HNBplYGAAk8nEUUcdNS5ENB/MVyhPFEWGk2n+0tGHuy9BpVaFQqHgPV+MvgR8bIUBrSK34dxYo8PdGyWdmfy8eXfysrJyWltbCQT8tLW1YTabaWxsmPXqSRJH2mUUaxYkwVB0gEAgeCBct2J8uK5Y8sarFRUVrFt3oEbIaDTR2Ng4+QyRiZMtZkQWlErm6BktjRGleCJOIBAgFApRUVGBs8lJVVUVgUCAPXv35Po+Ndoo16hoMqiQlMXbNE2Gs7YMBIGucJzB4QwlKgVrrRU4a6awbxJz15Q4zWUTS+UEJm//U6ZWsspcQSor0d0fh2wKITlIfCCLVF5JZYmSEgVIGejpTyJJI11wLZUopSxebzfBYA8lJRpsdQ1U1xoKjTFTGZFEWkSnVVte7GkAAGbpSURBVBXc4JVCvnZJonyyzElBKIT3xGzugwmCAkEQKNWoaDBUoZ5IoA+i2VhOdZmawECCVEZEX6ahrkqLRqVAFMVJtwa0Wi1HHnkkfX19tLW10dXVxerVq0cKy+fv+TRVKE/eY1pEYrEYkUiE1atXc/bZZ/P973+fdevWzdoapBjyK6bp2ppPxMHhuu5okq5oCmdtOZqRCyqTFfH2xfH2JVhpyoUdVUoljTVVuHv7c506D+LgB7BCoaCurp7qagOdnR28//52mpqaZm+Dn5WmXTlls1n6wmEC3cGiw3VFMarGKl8jZDAYcHV2sn17zkC1enRLd3IzWaFIi6NpT5/NZyrO7vX5pn4D0QH8fj8DgwPUGGpoXds6JqxcX1dPjeFA7ZPNnqt9ErICzFGclIKCltpyHDotybSERiUgAsGB1EgrcSX6UvX4ZBcJFNmpxUlZSHM/kF2oUigwV5ZgKFMTHk4TGiwhEBtGGghRqytnrcWAs7YctVKBSgFliizR3m684V50uipWrlyJLt9sTziwas2nwzfXVhQKZgXAWKGmRKVEOdX9OEF4r6qslHpDFcopwqMHYyjXYDgoW1CSpKKcH6qrq9mwYQM+n49du3bhdrtZs2bNvHXgXqo6pgUrf3S5XFx44YU4nU5KS0tpbm7mRz/6EalUasxx27dv52Mf+xharZbGxkZ++ctfjnuvJ554gtWrV6PVajniiCP4wx/+MOb3kiRxww03YLVaKS0t5fTTT2ffvn1jjolEInz9619Hp9Oh1+u58MILC0kOoijyxz/+kU984hN88pOfLDh95yuwF1KUgMKsaCbhPFEUyWQyZDIZstlcvFulUjGQEtGoVAVRgtwKSaUQ6B0amy6uUeXEaUzhJyPZbpM8tUpLS1mzZi11dXXs3buXjo52MpmpQ4KTkdsHGH/jJ1MpPB4P77/zHt0+PyaTiaOPPhq73T5/3lwj4pRHq9WyevVqGhsa6ejoZN++vYVrVSnlalPmE0kcCcXNAAVAOkswEGT79u3s37+fiooKjjrqKJqbmyfc69RqtbSsbsHhdOD1emlra2M4PoyQnUttmZQLZ2ZzDgaVWhX98Qx/7ejjLU8/73mj/LWjj12BQbITxTxHxGkyDOUaKkqUhGPpwqp6KJlBoRA4zlnNWetMHOeopqXByJo6AzVCDGEgQKUijUGVYrjHQ8feNgDWrVvH6tUtVFWNWl2PrNwg5xauVStQKQVWmcpZY6lktaUSa5UWffnEZrvjEAQEhQKTrgJLVTmimCWTycxpRZGfaBaTTCUIAg0NDZx88sno9Xr++te/snPnznHP2tkwVR3TIbnHtHv3bkRRZNu2baxYsYIdO3Zw0UUXEYvF2Lp1KwADAwOcccYZnH766dx333188MEHfOMb30Cv13PxxRcD8Je//IV/+Id/4MYbb+Qzn/kMjz32GF/4whd45513WLduHQC//OUvueOOO3jkkUdwOp388Ic/5Mwzz2TXrl2FB9nXv/51/H4/zz//POl0mo0bN3LxxRfz2GOP0dnZyde+9jWGh4c566yz+MMf/sBPf/pTrr32Wqqrq9m4ceNCfU3AgbbFxcyQstnsmGQGpVKJUqkc2YhVUKJWjfMFA8hK0oSFdVq1ioYaHd5wNNdXaSIXh4MQBAGz2Yxer6ezs5Pt27fjcDgwGAxTvm7iD5QL64mSyODQIIFAgP5IH3rdxNl184oEypGVU74/Um2+pbvHw/bt72Ovt2EymhZmDFlpXBfeycgkUwT9AXp6Qqg1aqxWKzU1NTlH92kQEKgx1KCv0h9otmi1UldXh0KtnPHK6WCH8ng6y07/AKm0iFVXgkIQGE5nae8ZRqdV06ifYHN+ipVThVZFq7WStsAggWhuMlWiVrDKVE69Plcg3KAvRcyKdARjeMIVeP1BOv+2D30JHOUwctRRR009oRypr0OlwG4oZWd3zvS4TK0kkckylMyyylxeVDt0pSBQV11JhbZkZOUkFSaZCoViVg/w/OtnslpRqVS0tLTQ0NDA7t27efnll1mxYgU2m21W2cL5SMxEY8h/zoVCkBby3Q9iy5Yt3HvvvXR0dABw7733cv311xMIBAoX0aZNm/jNb37D7t27Afj7v/97YrEYzzzzTOF9TjjhBI466ijuu+8+JEmirq6Oq6++mmuuuQaAaDSK2Wzm4Ycf5qtf/SptbW2sXbuWN998k4985CMAPPfcc3z605+mq6uLuro67rrrLm644Qa8Xi8VFRXs2rWLBx54gGeeeYa33357Qb8XSZL485//zIknnjjhikAUxcJ/QEGEVCrVuAsuOJDkT3tCaJQKqstyG7/9I9YxH2+pxTpBpTrAcCJJV2hwxhdbvoeU2+2mqqoKh8MxoyJAUczS2xsmEAqQTKUwG42YjGa0JQvjWjwhwvhNeQEYiPTT2elCrVbjzLd0X4jTT7HnNDQ0SI8/SLg3jL5Kj8VqyYn1HNY7sVgMl8tFOp3G7rCjr6kuSpwUkEtXO8jCvKs/ztueaEGU8oSGkhjKNRzvmCKtWZg8rJdIZ+mLpclKElWlKirz9j+ShBKBzp4hXtvdTTI2SJlaoLSiktBAgnKSnLy2HqvFPO0DWVBAWpJwR4ZxR+Ik0yIaVc5VwllTNmXGIkCJSkl9tY4S9dg5/ugHd34Cmf//YojH47z00kuceeaZs54UhUKhwnN0zZo1OQurGSCKIv/3f//HaaedNq7INi++JSUlCxLqW0SbzZxgjJ5Vv/7665x88sljZjZnnnkme/bsoa+vr3DM6aefPuZ9zjzzTF5//XUAOjs7CQQCY46pqqri+OOPLxzz+uuvo9frC6IEcPrpp6NQKHjjjTcA+Nvf/sbJJ59MaWkppaWlxGIxPvGJT7Bv377CWBaKvNAcnAAhiiLpdJpMJlPYCFWr1Wg0GjQazYQ3nalSw1ENVWQlcEXiuCJx0lmRoxt0WHSTV3CXaUuoq62cti5DkiTiqSyJ9IFVm9Fo5Mgjj0SSJLZv305vb++0ApdMJvF4PLz77nsEAgHMRjMfWX80tgb74ooS5Gbvo4abC91BVZWeI448gkpdJTt27MDr9ZIV5z+tX8qOPX+ujXuEXbt2sWfnblQKFUceeSQtLS1U6armXKRcXl7O2ta1WOustO9vZ9/uvaSSySlfo8wnW0zQVyNvpKo46OJRKQVSmWnC01OE9bRqJVa9lobq0lGiBOlEio4OF6++20Y6Eaep3kxzk5N6k5G1znrUVbV0dAXZsWMHg4NTt3+RRFALCpy15ZzUZOCjzQY+2lzDStPUafQAFSUa7LX6caIEB+5pQRAKYff8FkEx5Fcqc1mpG41GPvrRj9LY2Mh7773HO++8MyPzgHyI/kMVyjuY/fv3c+eddxbCeACBQACn0znmOLPZXPhddXV17qE18rPRxwQCgcJxo1832TEmk2nM71UqFQaDYcwxTqczV+U9YkuUf01PT8+CF7PlEyAmqj3Kh+uKmZkIgsAaayVWvZbeoVyMubZCU1RacEVpCRZDJf7wxDdzZDhFR+8wfbE0CgGMOg0raiso0yjRaDSsXLmSvpEC1nA4jNPpQKM5IIaSJDE4mMuu6+/vQ6+vZuXKFegqdShEoVC8O23Du4VABKUggWJsmEqpUGJrzLd07yQSieBwOqjSzTLpY4rzi1KGYKiHYCCIAJiNZkzNq+atLGE0AgJmk5nq6mq8Hi8fvLudensDZsv4diHKkezMyUK8FSUq1Ipcp9v8nowoSQynshOH8Q6miIQIgOHBIfw+P5FIH7oqPQajlbJSbcF9AnLO42qNFqdtFcJwP7t376a62oDN1jhpaK93IElPLEE8K1E1if/dwdRUlGHSTV+/mL9/ZxremyojbyYoFAocDgd1dXXs27eP1157DbvdTnNz87TX1Uz2ueabGV/xmzZt4qabbprymLa2NlavXl34t8/n41Of+hTnnHMOF1100cxHucjk26vPtXB2JigUClKpVGHJPFqQZnNh6EvVRYnRwejKtYiiRLBvrPvFQCLNe11RYoksVaVqREmiszfX/O4YexWakdmdwVBDZaUOj8fD9u0fYLM1UlNTSzjcSyAQJJVKYTKZWL/+KEpKSka5k0sIQj6VnEVqNXiAXNKHAFkQFeOTMspHUuaDwSB79+zFUGPAbrPPi2gkEomRdO8eyiorcNjs6HX6RXkgaNQampubqTXW0unqJBQK4WxyUlFRWXR6fHW5mvpqLa5wHK0qg1KhIJbMUl2uob66yOLPycRppCA20O0nNjSMyWhi/fr1lJRoiLr6icTSVIwKBCQyImqlgnKNiurqnCO7x+Nm+/btNDQ0YDKZxnyvnkicXf5BUtnc69ziML5ogqMaqiZsSaIQBKz6SnSlM/OPy6+gpBF7KIVCMaVAzXc2nEajobW1lcbGxoK90cqVK6e0N8rXMC2W/dFoZnxXXX311VxwwQVTHtPU1FT4/+7ubk477TROPPFE7r///jHHWSyWcU7e+X9bLJYpjxn9+/zPrFbrmGOOOuqowjE9PT1j3iOTyRCJRMadRxAEKioqxoQADl5tzSeiKBYuwnzbAY1GU7iQlwJ9ZWnOLqX/wLLfH00ymMhQV3Cnzm0UBwaT9A6mqdMfuInUI03uenp6cLvduFwuSkq0WK2WEdsmJSCNuHGPlSCBUa3CF+XT5kXpQCq4UprYOilffV9dXT3S0v197DY7NTU1M755JUliYHAgl+zR30+NoYbVa9agK6vIefHN+VPNjCpdFUcecST+bj9tu9ow1tbS2GBDrZz+EaFAoNVaib5Uja8/TlqElfoSGqvLqCyZwSNmlDiJWZFQKEQg4IesiNlkoWXl2K7CtupSIrE04ViKihIV6axIfzyNzVBK1cj+qlab6wzd3x/F5XLR09ODw+FAp9MRT2fZ1zOESiFQW55bJYmChG8wiSs8zLr6sSnXaqWChmodWs3MJ3xwIPSV33/KZ9NO9PDPZrMLcv/rdDqOO+44gsEgu3fvxuv1smbNmpE2J2OZzo4IlpElkdFoLLrTqs/n47TTTuOYY47hoYceGvdFb9iwgeuvv550Ol3YMH/++edpaWkphM42bNjACy+8wJVXXll43fPPP8+GDRsAcDqdWCwWXnjhhYIQDQwM8MYbb3DJJZcU3qO/v5+3336bY445BoA//elPiKLI8ccfP24s+SLbt956i5UrV857GG+icN3q1avZs2cP77//PuvWraOiovieKQtBja6MbFakbzDnHhGNp9GqFGMuxHxr5uHUgU2C8eE6PQD9/VGyWTFXhAgIojDpVFwAyEpIysK/Fox8EfHokUhivsZq4teUlOQedpFIBJd7xHfP6SzKhTkrZomEI/gDftKpNEaTEYfDQYmmZGR1ksuMzBUgLy4KQUF9fT21hho6XR1sf+997HY7NbU10+5rqRQK7IYy7IYyJGbvJJ9KpQgGgwR6g2jUGhqtDRgMhgkf0taqEkSpks7wMIPJDCqlwApTOStMFeP2u/T6Ko488gj8/gB79uyhutqAttrMcCpb6K8EuYxDvUZFz2CSTEZENZLJWqZRU1+tm3bfqRhGC9TBCU35+2su3WuLOX/e3qizs5M333wTs9nMqlWrxiRfLVUNEyxgVp7P5+PUU0/FbrfzyCOPjPmA+VVKNBqlpaWFM844g+uuu44dO3bwjW98g1tvvXVMuvgpp5zCL37xC84++2z+8z//k5///Odj0sVvuukmfvGLX4xJF9++ffuYdPGzzjqLYDDIfffdV0gX/8hHPsJjjz02bix79uxh9erVPPnkk9x4443zli5+cHZdfjmfD9dls1k6OjrweDw0NTVht9uXbNWUJxAZJDqUYEf3AK7e4THxd1GSCAwkOapBR4O+hN7eXLgunU5jNBoxm82Fh/XAQJSOjk7UKhXN9ibKyooJ8Qjz4lIwEZKUc3mbzBUcyK1cpnm+ZjIZPF4P4d4w9Q31WCyWCXtYpdIpeoI9BHuCqFSjnM8VyoIQj2ORxeng76Q3GsHtdqPVanP1iNqF82Qbjg8XmhXqKnVY6yy5fbwiZuSZrEg8LaJSCpQWUXeUSCTxeNx4QgMEpSpW1NWMqeUbSKQRFAIfXWVApVRQXabFXFWxIKuD/OopX1yfXz0FAgHcbjcnnHDCvJ/zYOLxOHv37qWnp4empiYcDgdKpZJgMEh7ezsnnnjiuNfkn2FarXZBvpcFE6aHH3540gf66FNu376dyy67jDfffJPa2louv/xyrrvuujHHP/HEE/zgBz/A5XKxcuVKfvnLX/LpT396zPv96Ec/4v7776e/v5+TTjqJe+65h1WrVhWOiUQifOc73+F3v/sdCoWCL3/5y9xxxx1jVib5sfzlL3+hoqKCq6++mu9973tz+h4mWh3lxWiy2Ug0GmXHjh2oVCpaW1uXfPXU3TtAZ88Ab3v6ERDQj+wxRYbTaBQSNm2CgUgvGo1m5IFbM7FdUTaL1+0lGOyhrq4uV0ejmOaiFkbMN+fx4hdgJO25iGOLdEQfGBygs6MThUJBU9OBlu6x4RiBQIBwOIyuUofFYqGqqqpwMyukqcVx8cRJmmA/SSBDhq4uH8GeYKH2qZjaqeLOmHPpD/gDRAei1NTUYLVaKS8ty9W3jdR4LVS4KBTu49l3O0lLAisbzZRpc47f/miCVeZyWuurMOnL0U9iwjqfjE4vVygU+P1+/H4/xx577IKfO0/e3iidTrN69WoymQxdXV2FqNJoRFFEEIT5K3g/iEWtYzpUOPfcc7HZbGzevHnW7zFR7dFMkhmy2Szt7e14vd6CA8VSbEJC7qbx9Q6wpzvK/lCMwUSaVDKJlBxCTwybqRqLxUJlZeWEY5SkXMw4/wAeGhqio6MTyO1HVlRMk2RSqDOa++c/kGxRPMWKkyiJdPu68XX70Ov1ZDIZYrEYtbW1WCyWg+qgpIK10LQssDhNumLL/1IhMBSL0dnZSSaTweFwTLgnUSyiJBbCmalkCpPZhNlsRq1Wj2q4OHL6BRYnX/8wf2nrIhiOUl5ehl6vx1JVyjH2apqt1ZSVzG4/abZIkkQ6nWb//v0kk0mOOeaYRb3vJUmiq6uLffv2oVKp0Gg0E67aZGFaAr797W+j0Wj42c9+NuPX5pMZ8kvzvCDlw3Yzpb+/n507d6JWq2ltbV3UTMHRiKKEOxCh3ePD5eshm0ljrzNSb7WMSQk/mNx+0vjViShKdHf76O72j3RgrZ/aX0wQyAqzXzhJI0JAMUIw0emV0yckZLNZQqEQ3f5u0uk0SoUSp9NJTU3N2PdCGjHKm8FYFkicpl2xQUGcRCR6gj14vd5xfZ+KIZPJ0BPqIRAIoBAUWK1Wao21IyswKVcyMMHjaKHFaSCRpjsSw9vdTTYxzPoVDWxYv5qSWSY5zJZ0Oo3X68Xr9RbKL2pqambtHjHXsbzzzjv09fVhs9lYsWLFmHT7fDr7QnW3lYVpAq699loikQi33XZbUcdPFq6byJlhNmSzWfbv309XV1fBYmQxL9Lh4WG8Xi9dPh9DaQU1tSZqagzTuosrpNzqZKqhxmLDdHZ2kMlkaW5uprJyirClIJCdIJV7WqSR1clcL/VJxCGZTBbcvbVabS5zz1BNb28vXo8XvV6PzW5Do9bMasWWR1LO39+8mD220QhCvk26QCqdwuvxEumL0NjQiMlsmnBfLU/+++kJ9VBWWoa1zkp1dXXh71iMUC+0OOXJJuOEAx5USiWrV69elGZ8iUQCt9uNz+dDp9PhcDgKk5m5uEfMlf379zMwMIAkSfT397NixQoaGxtRKBSF5IyF8hGVhWkC/vmf/5ldu3bx4IMPTnncXMN1M6Wvr4+dO3dSUlJCa2vrpC2P5wNJkohEIng8HsLhMCaTCZvNRnlFJV2hKKn0VA4IM1udiKJEIBCgq6sLk8lIQ0MjqslaBsxQnAQpt2Kbr4s8v3KSJKng7dfX14eh2oDFYqGiYuwmeSqdwuVyEe2P4rQ7MBpq5xaRnKcar3wG4EwYLU4A0YEork4XCqUi18/qoL3QoaEh/AE/kUiE6upqrFYrlRVje17NRKgXWpyMVeUYdGWIoojH46GjowOTycTKlSsXZGUwNDSEy+UiGAxSW1uLw+GY0K0/n703OgKzGOK0Z88estksa9euJRQK0dbWhkKhKHTPlYVpkdm6dSsvvfRSIWPvYA42Us0nMyxG7VE2m2Xfvn10d3cXZjDzeZFmMhn8fj9er5dUKkVDQwMNDQ1jYsnpTBZPsH+kg+lYcqE7ZtW0KB5P0NHRQSqVwul0otdP4q5Q5J5PUWGqGSKJEpFoBJ/fn2vFYTJiMVumfnBJEv2RPlwdrkKGm7Z0DrH5OYjTlPtJxbz+IHESJRF/tx9ftw+j0UhDQwNDQ0N0d3czPDyMsdaIxWKZcC9itvt98y1OCkGgrlZHuXbsQzaRSLB3717C4TBNTU2F1cJcyK8+XC4XkUgEq9WK3W6fNkSff0znQ2iLEd7LbyHkk8hEUcTtdtPe3o7BYOCII45YsMQsWZgm4L777uPxxx/n6aefLvxsJkaqi0EkEmHnzp2Ulpaydu3aOa+e8uG67u5uSktLsdlsmM3mSTMHU+ks3p6x4pQXgrncKpKUK472er0YDAbsdtvERX5TiNNMw1TFkElnCPYECQaCKJUKLPVWaozGaes8RhfvZrNZvF4voZ4QdfV11FnrEKbLSpzoPQWQFDPfc5pLGPHg8x+cjBIbjrF//34S8QRKpRJrnRWzabIuzzNI/Jjo/PMoThqVknpjFZopmvqFw2H27NlTqDecTXhPkiRCoRAul4tYLEZjYyONjY0zXomNTi9faIHavn075eXlNDc3j/l5MpnE5XLR0tIi7zEtJo899hi33nproQh3tPni6Lqjpa4xymQy7Nu3D7/fz8qVK2loaJjRBTpZuG50OvNUJFMZPD39iKJU1H7STEgkkrhcncRiwzidTgyGCR4Gk4iTQpTm1mV2FPHheKG+prKyEovFkstIE5g2IWEyIRgaGqKzoxMJiSZnExVT7atNQk4civuyF0Ko8+KUzmQIBoIEg0HUGjWVlZVEwhFKy0onrH3KrdhgrtVpo8VJkiSiiQzprESZWjl519mDqCjVYDFUjqlhmozR4T2j0ciqVauKeiiLokh3dzdut5tsNovdbqe+vn7OVlYTuZfPtzi9++67VFdX43A4xv0um82iVqtn1ElgJsjCNAG//e1vue6663jttdeA4mqPlpJwOMyuXbsoKytj7dq1lJZOXXeRyWTo7u7G6/WSyWSor68fF64rlngyjS8QRZpBk8NikSRGWmq4qKrSj7TUOOiGHpUtN9cw1YET57IhA4EAg4OD1NTU5NK9y8vGHYdqvDhJSOPSnsedQpTwB/z4ukZCYI0NM35YCeS95aZ+IM1mP2k6EvEE/oCfnr6RglirFV1Vrh1HNpulq6trXO3TvP19RhAUAkPpDLsCQ4QGU2REEa1aSWO1lhWmclRTCE6NrozaqplnuObDe729vTQ3N08a3kun03R1deHxeFCr1Tgcjlzx9TxPZkcX5x7sHjFX3nzzTaxWKw0NDeN+J4oiarV6QQyGQRamCbnrrru44oor+I//+A/OPPPMBUtmmE8ymQx79+4lEAiwatWqCc0ZY7FYIVxXXl5OY2PjvNwsseEU3cEoC+Vul0qlcblcDAwM4HDYqampHbsyUwg5V/I5PvTErEioN0QgECCbyWK2mHPhqAnaGhQYJ06Tpz1PRCKRwNXpIh6P51q6T7QynBIBSTmx8/d8CwFSrpDY7/czEB2gpjZXEKutKJ3w/LFRtU9OuwP9PDuySxK87Y3iHRimtkJLiUoglswykEizrl5HU+144REEAauhksqyuYWgIpFIodfR6tWrC+18EokEHo+Hrq4uKisrcTgcuXb2C7gXtFDhvb/+9a/Y7fYxHqR5stksGo1GFqbFJBaLceedd3LjjTfyd3/3d/z85z+nsrJy+hcuA3p7e9m1axcVFRWsXbuWkpISwuEwHo+HSCSC2WwuhOvmk6FYEn/PAAtpvRoO51pqlJeXj3jTaQq9lKSROpvZkErm/NmCPUG0Jbl075qamhnt/0hKYfZCkF8ZetzoKnXYHfYZZjsJIwkRB5iv/STIre7CkTABf4BEMoHZZMZsMRfGKCgEskxcYyZJEr3BIB63l6oqPXa7bd4yufriaf7a3kdVuQqVWlHI1OyLpyhRKTmxqXqMt51aqaS+VkeJZn4epqPDe/kstVAoRE1NzZyLkGfDwe4Rc109vfrqq7S0tEzojSoL0xLS3t7Oxo0b6erq4v7772fDhg1L5r4wE9LpNLt376anp6dw4eSz6xZqsxJgYDBBsHdgwd4fcitDl8tNf38ftkYbphrjgbm6UoFYRJvyPEODQwQCASKRCHq9PpfOXFk5q3RuhZSzLp1LL6lMOoPb46avr4/GxkbMJnPxYxFAUuTHMvvEgtFks9mcv18wCAIF48+JwtkTidNo66d0Oo3b7aavr5/GxgbMZvOc76WewSRvuPqw6rQwki0okGvrnsqKnNRcg1ad+1JKS9TU1cyPCeto+vv76ejoIBwOIwhCoRh1KSMso9PL5yJQL730EkccccSY5q55RFFEo9EsnNGsLExTk81mufnmm/nnf/5nvvWtb/GDH/xgwWw45oPR4bqSkhJSqRQ6nY7W1tZFGXd/dJhQZGj6A+dItK+fzv0dlGi1NDmdBz6bamqHBkmUiPRFCAQCxIfjGE05s9lZfzfSSBvorJQTB6WCuVZNRaNROjs7UavVNDmbKC3K8DaX9izOw+2cTCYJBoP0BHsoLSvFarViqDZMK5LCKHeOyVaP0Wiu/YRCocTpdMwp3XgwkeH1zj60KgVlGuVIMoxE71CaqjIVJzirUQgC+opSTPryeZtUSpJEb28vLpeLoaEhGhoaaGxsZHh4eMLw3lIwH+G9P/3pTxxzzDHjoisL3VYdZGEqmu3bt3PeeeeRzWZ54IEHOPLII5d6SAXyN4rX66Wvrw+z2UxjYyNVVVWk02n27NlDKBSipaUFq9W64Ku+cF+MSH/xLZxngjRKCArp16EQDQ0NWCyW3GebQJwymUxh9i8oBCxmC0bT9OneUw+GQk+p0YhKYVarrjHvIYr4unwEAoFcAkF93ZSz8Hzobrap5JCb1Pj9IwWx+lxB7EwzBhWK3KpxqjCiJEl0d3fT3d1Nba2RxlkkfuTZ4R+kIxSjXKOiRKUgls6QBo5qrKJer8ViqKSqfH4mZKIoEggEcLlcpNPpQobd6My00eG92traca0kFpuJsvfy/z8d//d//8eJJ544bvIgC9MyI5lM8uMf/5jbb7+dzZs3c8UVVyxYjLUY0uk0fr8fj8dDNpudMlzX09NDW1sbOp2usPe0kITCQ/QPDM/7+yqy4zPMBgYH6ezoQKlU0tTcTFlpKZIy94BMxBMFu6CKiopCo7+5CkcuXCYyYeRQyO05zceNNTw8TEdHB9lsFqfTiU6nG3eMAiAz6mzCDNqFjGQg+v1+hoaGcgXDkxTEFvNeSgmkvCP8NCQSCVwuF8PDw9hstvFJLUWQFiVc4RhdfQkyWYnyEiX22jIaaspoMFZROg8mrHmXbY/Hg1KpxOFwYLVap5woJBIJ9u3bRygUoqmpCZvNtmzCe8Wkl0uSxP/+7/9y6qmnjrsW8mJXUlKyYJ9JFqYZIkkSr732Ghs3bsRoNLJt27ZxBWgLzehwXUVFRW4/wmye9iJJpVLs2bOH3t5eVq9efWCFsUAEQ4MMDMXn5b0ESQBRnPRpmxVFfL6RFYbFQkVlJYHeIAMDgxhqcnZB82WAq5CYPslhJuIwHRIEggG6vF0YagzYGm2o1KoDrc8n2E/K1fkwqQCLojjSPytAJpPBYrFgMplmP9E6aPUoKASyRTyzJAkikTBut5vS0jIcDgels3DFSGclMqKIRqWgXKuhzqSb3NaqSJLJZCHDrry8HIfDgdFonNE9M1n23lIwk/BeJpPhj3/8I5/4xCfG1SrJwrSMGRwc5Nprr+Xf//3f+fnPf87GjRsXdEY0VbhupgSDQdra2tDr9axZs2bBVk+SJBEIDTAUS87pfYRihICx4iSJIrVGIw0OG+p5comeSggme4GomHtYL0++4n5oaAiHzU5tdc3Ub50vQB51UCadIRAMEAzmOsTmGxbOxoGicBpGwogHfS3FihMcWJWEQqFC7dNs7iddhRZz7cTtV4olFovhdrvx+/0YDIZCht1s31MURbxeL+3t7csqvDeVQCUSCV588UXOOOOMcX8HWZiWOZIk8eyzz3LRRRdxxBFHcM899xS6884X6XS6UAwrimIhXDfXlNtUKsXu3buJRCKF1dNCIEkS3cEow/HULF47KrFgCpKpFD3BID09Pag1Gsxmc8HR2mIxU29rRJhjNlbOWoiZewDOY1gPyIXeImE62zspLyufvqX7SAFyIpHA7/cfcLCwWtBX6ecsmkpp6v2kmYgTjK19mknKtSAI1BrKqdYdKIIeTmVJpLNo1cpccsQ05BMzent7MZvNOBxzS844mGQyyd69e5dVeG8y94hYLMZrr73GGWecMenrFqp7LcjCNC+Ew2Euu+wynn/+eW677Ta+9KUvzfkPNjQ0hNfrxe/3U1lZSWNjIyaTad4v5PzqyWAwsHr16gVxCxZFCV+gn0QyPYNXCQjZyUN3kLt5AoEA4UiEKl2uO6xOpyt898PxOB3t7WSzWRwrm6nUza4WbdwezkyZx7CeQhIgK460dPcSDoepr8+3dB97zUnkVvb+oJ++UR1i58WVvshJA8xcnCQJenpyfonF1D4plQqsRh1lpblj0lmRnd2DtPfGiKdESjUKmmvLaa2rRK0cP/sPh8OFAu76+nrsdvuCrmgikQh79uxBkiRaWlrG9etabCZyjxgYGOCtt97iE5/4xKTHy8J0CCBJEv/xH//Bd77zHc444wxuvvnmGZs95o0evV4v/f39WCwWGhsbJ9zwnk9SqRRtbW309fWxZs0azGbzvJ8jK4p0dfeTSmemPVZg4tAQjPj79fURCAQYjsUwGnPp3pPZMEnSSEsNXxe1FhMNjY3FZxLlPebmw/h0mj2faV/PxCHNgcFBOjtHWro7nZSXlyNKEn2RCH6/n0QigclsxmI1o9LOU8h2kmzEKVEW5wg/mnztU39/Pw0NDZjNlnHJESUaFVZTFRr1gb/pe94o73ij6EvVlGuUxFJZ+uNp/l9jFUc15kLfoigSDAZxuVykUilsNhsNDQ0L5v12MMs9vJdvUHrKKaeMOzZvZC0L0yGE1+vlm9/8Jjt37uTee+/l4x//+LR/vHQ6jc/no6urC1EUaWxspL6+fsF6nUyEJEkEg0F27969YKunbFbE291HOjNxLydpCiHIZDKEQjm7IACzxYLJaCx6sz6RSNDh6iSeSuJsck4fIprNw3c6FMKIK/fMmC6MKEoS3T4fvpFkmFQqhcAEBbGzEIeDKaySZvO1zPL8k9U+VZaXYK7VoRi1PzacyvKHHUEUgkB12QGR6RtOIyHxyZYa+nuDuN1uBEEoZNgtlQdmMplk37599PT0LJvwXiaToaOjg0gkwkc/+tFxz698dl9JSYksTIcSoihy3333cd111/H1r3+dn/70pxNmhA0NDeHxePD7/eh0Omw2G0ajcUkvzGQySVtbG9FolDVr1mAymeb1/dOZLF3d/WSyY8VJmkQIEokD6d5lZWVYrLnupweHrYpBkiRCvSFcXV6qDdXY7fYJhS3fqmIh3JVmGtYqJoyYTKVyHWJ7enKvEQSampupnkh85yBOCgTIzNGsd5bnz7t0+/1+amuNHHVEC2bj+MSfcCzFszt6MFVqxoTthpMp9nqDNKv6Metz2X8mk2nZOLn09fWxe/fuJQ3v5Y1n3W43Wq2W5ubmQmv30e4ReWFayBWeLEwLyN69ezn//PMJh8Pcf//9HHvssWSz2UJ4YjHDdTMhH/7avXs3RqORlpaWeQ1xpFIZvP7+QkgAxgqBJEkMDOa6w/b391NjONAddl7On0nT7uokFovhcDgw1BxI4Z2Xh+90FPlwni6xIF8QGx7VIba8vDwXDvZ4qNLrsdvtaA762wkKBVnFDG77GewnFcOMzz+KZDJJNNJNNp1g1apV40oeYqkMz+7oQSkI6MvUJFNJenp68AYjlJaV8/cbmqkzLayp6mwRRZGuri7a29upqalZtPDe6LT4iooKnE7nmNbuB2fv5f+9kLWQsjAtMJlMhptuuomf/exnHHXUUXR0dPCxj32MH//4x4serpspiUSCtrY2BgYGWLt27YRmjrN+72Qanz8Kolh4+IqSRLi3F38gQCqZxGQ2YzabKVmI70iAnkh4jHFqqVozb8an055+qpXTFEIgMbYlh9GYK4gtPegBlhrZn4n292Oz23P1N6PPrxzZ85punORa00/p8zQLij3/aNRqJfWmKtRqJcFgkD179lBRUcHq1avHRCTe9UZ5fV+QTKyfZGwAbYUOVXk1J6wwcXTj/JoXLwSjw3tOpxO73b4gUZR4PI7b7cbn82EwGEa6RuvHHXdw9l4+g08WpkOYDz74gDvvvJNHH30UhUJBbW0tjz/+OOvXr1/qoRWFJEn4/X727Nkz76uneDxFd3c/yWQu3Ts4Yjqbr60ppoHbnFAKJDNp3C4XA31R7I22BW9RcPD5D145FcKZB92V2YMLYs1mTGYz6mn22Pr6++ns7Cy0dB8jYNOs3BTkMgAXyjB+JuJUVqrBatKNuSbS6TTt7e34fD4cDgd2u51oNMr+jk62d0VJlugp11VTWaal2VjOugmy8pYz+fCeKIqsXr163sJ7+ZT8YDCI0WjE6XQW1T0hn8H44IMPolar+eEPfzgv45kIWZgWkO7ublatWsVXv/pVLr/8clpaWrj++uu57777+OEPf8hll122LBsPTkQikWDXrl0MDQ2xdu1aamtr5/yeg4OD7N3bwd493kJ32GK7584XErk9mXAkQmdnJ+VlZdPXBs0no8Qhnwo+mnQmQ08wSCAYRKVSYbVaqampmZFoH2jc10N9XR3WurrCHt1k4jDnFPliKcIRvrqqjNrqyU1Y+/v7+eCDD0gmkyiVSmw2G42NjaRRFNLFy+ep1cViMzq8ZzAYaGlpmXV4b2BggM7OTnp7e7Fardjt9qLdUHp6erjrrrt44IEHOOKII7jhhhsmrHGaL2RhWmCGhobG7I1IksRLL73Exo0baWxsZNu2bdjt9iUcYfHkzTf37t2LyWRi1apVM1495VPiPR4P0Wg051xtMDM0OH0a+XyjAKSMiKBUIAq5sKvb4yESDmOz2RZtc1xQKXKhklGhu/iopI/KykqsFgtVev2c6mGHhobo6OxEkiSampqozF+Xo8VBYqT77gLvs41mEkd4hSBgqq1EVzHxgzibzeLz+QoZdjqdjt7eXmpra2lpaVm8ycUiMNvwniRJ9I+smvv6+mhoaJhRnZbX6+X222/nkUce4aSTTmLz5s2ccsopC35fyMK0RESjUa666iqefPJJbrrpJs4999xl3yU3TzweZ9euXQwPD7N27dqiQgz5du4ej2fClPhoNE6oZ2F7OeWRyCcWjEq+GBGn3FiidHR0oCkpocnpnLZV/VwRRCnXT0gYKYj1++nv76e2pgaL1Ur5fBTEjiCOhGZ9vlxL98aGnLO3MCJOs3K3mA8OEie1SonVpEM7gQlrKpXC6/Xi9XrRarWFDDuFQkEymWTPnj2Ew+FC6/PlmOgwW4oN7+UtzDo7c0k+jY2N2GzFNWmUJIn9+/dz66238p//+Z98+tOfZvPmzXzkIx9ZtO9SFqYlRJIknn76aS6++GKOO+447rzzznlPz14oJEnC5/Oxd+9eLBYLq1atmjD1Oh6P4/V68fl8lJWVYbPZJjWc7euLEe5d2F5OheZ1ExmfjhKnfEuNnlEtNWaToj7tWLI51+e+SAR/KEA8scBJHyMkEgk6XQdautdUG5AQ86NaEvJhxVKtGqtxvAnr6M16vV6fy6g0GCZ8WIbDYdra2lCpVKxZs2beOzYvJQeH91atWlWYPOXrETs7O0mlUtjtdhoaimsrIkkSO3bsYOvWrfzud7/jnHPOYdOmTaxdu3bRxV0WpmVAT08P3/72t3n11Ve58847+cxnPnPIzPLi8Tg7d+4kHo/T2tqKwWAohA88Hg+hUAij0Yjdbi9q/ygcHqIvsjC9nARGQndTHaRSjNnrH91Sw9nUNG+rFwHIJNOEQj2FomGLxYLJakGxSPuOErmW7l6Xi4qychwOJ9oy7Xwn4M2IKn0ptQeZsA4ODuJyuQgGg5hMJhwOR1HlFdlsFpfLhcvlor6+nubm5kVzdlgMRof3HA4HarUat9uNJEk4HA7q6uqK2sOWJIm//e1vbN26lT/96U+cf/75XHvttTQ1NS3Zc0gWpmWCKIr827/9G1deeSWf/exnuemmmw6ZWZ4kSXR1dbF37170ej3pdJp4PE59fT2NjY0zDoWFQoNE++e3l5MAxdcnqQSkUfI12rW8zmqlrr5+1qsnCcgkkgT8AXp6gmi1WqwWK9UGwwEHA6VioRLhxo1FIUE6mcTj9hDpi2BrtGGus86pRfysEASMxgqqqnLCL0kSfX19uFwu+vr6qK+vx2azzcrnLxaLsXv3boaGhmhpaZmXtu7LhWw2y759++jq6gKYUWt3URR56aWX2LJlC2+//TYXXXQRV199NfX19Qs97GmRhWmZ4XK52LhxIx0dHWzbto2Pfexjy/4mSqVS+Hw+PB4PmUwGpVJJa2vrnOqegsEogwOJeRidhGKaQtWJEFSKcSuHWCxGe0cHAE1O54wLfodjwwS6ffSGwuj1eqxWK5WVFRP+fQXl+PPPN4IojdlPivZH6XR1olapca5oprR8/va2pkKpVGC2VFFWpkGSJHp6enCNhBkbGxtpbGycc71fPsQ1We3ToUY6ncbr9eLxeCgtLcVut5NMJuno6BgX3jsYURT5wx/+wNatW9m/fz+XXXYZV1xxxbxk2s4XsjAtQ7LZLHfeeSc/+MEP2LhxIz/+8Y8XfAN+Noy2VNLr9SNdSGvo6upi//791NXVsXLlylmlxOfcJ6LEhubYy0kUZ18cqhq/chElCX93N77ubsxmMw0NDVOmbkuSRDQazXWI7R/AaKzNFcQW8/dUKRYsD0HITvylZLOjVocNdVjq6xe0nqykRI3FWoVCkSuvyIei7HY7dXV1894h+uDaJ4fDcciUbMABlwav14tOp8PpdI7ZZ0ulUuzbt49gMDguey+TyfDf//3f3HLLLYRCIa688kouueSSZRmZkYVpGbNr1y7OP/98hoaGePDBBzn66KOXekiFIjuPx0NfXx8WiwWbzTauQC8Wi7Fr1y6SySStra0zdlrPn6vb1098Fr2cFIA43X7SdOdnJJV7gt8Nx+N0dnSQTqdxNjVRddCehziSFeX3+8mm05hrcy7oM97jmOewnkLI7bNNRyw20tIdEccEn28+qKjQUm0oxefrwuv1otFocDgcRXVjnivRaJS2tjYymQxr1qxZ8tYT0xGPx3G5XHR3d0/p0pCnv7+ft956i+uvv54rr7ySRCLBLbfcQjab5eqrr+bCCy+cn/YnC4QsTMucdDrNv/zLv7BlyxauueYarr766iXZwM1ms4WGhel0moaGhmlDLJIk4fF42L9/Pw0NDaxYsWLGs1NRlPD5+kgmiuvllNs3kebN100CUE38kCy01Ojqora2FpvNhiiK9PT05ApilUrqLBZqqmtQztJxQJJAUM995SQBSqQZhTRzny+I1+/DUFODzWab1mmiWMor1AwMhPD5fOh0ulxmYE3N4hZXS9K41hPLrfZpaGhoXOJHMS4NkBPfCy64gOeff56ysjJuuOEGrrzyymVtg5ZHFqZDAEmSeOONN7jgggvQ6XTcf//9rFq1alHOnUgk8Hq9dHV1UVpais1my6VOz2BGG4vF2LlzJ+l0mtbW1qK7kubJhZf6SCWL6OU0SSr4XJhKnCD3HbW3tzM8PIwEVFRUYLVYMFRVzYudjyRNff5iOHg/aSYkEkncXjeDsRh2u52a2tpZr0QTyQSJeB/RgTC1tbU4HI4lDyUlEgn27t1LOBxmxYoVNDQ0LPm+bjQapbOzk3A4jNVqxeFwFL3C6e/v5/777+fuu++mvr6eSy+9lL/+9a88/vjjbN68me9///vLXpxkYTqEiMVibNq0iYceeoif/OQnXHzxxQsW8ohGo7jdbnp6egqrgerq6lnfsJIk4Xa7aW9vp7Gxkebm5hmtnjKZLL6uPtLpiXs5AdN2vJ0TAkgTdD8dGhrCHwjQ19dHeVkZ8XgcQ3U19obGeV3ZStLkYcVphj2yepzbFyNJEpGBKJ0u14xtm/KddEM9ARDiNDbWz8gOZ7HI1z6p1WrWrFmz6I7/+UzEzs5OotEoDQ0N2Gy2ol0aQqFQwTaotbWVzZs38+lPf7rwjHj99de54447ePTRR5d92rwsTIcYkiTxwgsv8I1vfIOVK1dy3333zVt6Zz4M5fF4GBoaKqR7z2csemhoiJ07d5LNZmltbZ3RbDmdztLVFSF70B5J3lpowRkRJ3HkARLw+4nH4xhNJiwWCyUaDelkko797cRiwyPhKcP07zsDJJWiaI0p1G3N0+RfkiCLiHualu6F48k5Ffi7u8mKKdata8Zuty27cNlolqL2KW/T5XK5iMViBa+/Ylc1XV1d3H777Tz88MN89KMf5Z/+6Z8WxTZoIZGF6RClr6+P7373uzzzzDPcfPPN/P3f//2sL8R8B12v1wvkaiHq6uoW7IYURRG3201HRwc2m43m5uaiV36pVAZfVx/ZrFiowznY+HShyGazhHpD+ENBJGmkINZkQqlUHhiLKBYSRNwuN5Uj+ycazTx+l9MkROT2k8ZaLs0XuZWbkujgwLiW7nnEkQdtwO8nK4q0tDhobV0x7xl2C8li1D4d3N59pi4N7e3tBdugT33qU2zatInjjjvukBakPLIwHcJIksSTTz7JJZdcwimnnMKtt946o1qEWCyGx+Ohu7sbnU6HPd+3Z5Eu7MHBQXbu3IkkSbS2thYdOkkk0vh8fbmC2XneT5qIZCpFMBigJ9hDibaEuro69LU1Y8R0oj2cdDqNy+UiGo1it9vnsaWGgKQSJl05zWU/qRjye175lu7dfj9mkwmL1VpozaFSqaivr2PNGmehaPZQI5/csnfvXioqKlizZs28RA/y3XhdLhfAjNq7S5LEzp072bp1K08//TR/93d/x3XXXce6des+FIKURxamDwF+v5+LLrqIt99+m7vuuotPfepTk16kkiQRiUTweDyEw+FCuvdSddAVRRGXy0VnZyd2u52mpqaiVk/x4RR+bwRpAYUpNjxMwO8nHAlTpavCYrWi01UiIIAgICnJ/f80K5NIJLdvUF5ehtPhpEQ7D6EsAaSDvqf52k8qhtF7XtFolPaODtKpFNqRBJnaWgNWqx6tdnnvZRRDOp1m//79dHd343A4cDqds9rbzWQyhdblarUap9NZdGq8JEm89dZbbNmyhRdeeIHzzjuPa6+9lubm5g+VIOWRhelDgiiK/OpXv+Lqq6/mK1/5Cj/72c/GpJVms1n8fj8ej4dUKlVI914u8f7BwUF27NgBwLp164pKiY0NJQh09c3rc1hCItofxR/wMzg4SG1tLVarlVLt+IJYQcgt2Ip5LmQyGdxuD5FIGFujDZN5HlpqCALSiI3RfO8nFcNwfBh/sIfeSJiqqiq0Wi2hnh6Mpho2bFhPWdnyKwqfC/nap2w2O6PGfXk3dI/HQ9lI4kixkQlRFHnllVf45S9/yZtvvlmwDWpoaJjrx1nWyML0IaO9vZ2NGzfS1dXF/fffT11dHY888ggnn3wyJSUl2O12LBbLsqx2F0WRzs5OXC5X0TPTwWicnu7+uZ9bEgmHw/j9ftKpNGazGbPFjFo1fsYvAQpEpIyEoBQQBUXRglCw/VFraGqaj5Yawkg18eLdxoODg3R3+4lGo9TUGKizNaAdEW5tqZJw2EckEmHVqlXU1dV9qGb0M6l9SiQSeDweurq6qKqqwul0Fp3ZKooizz77LFu3bmXfvn1ceumlXHHFFXOy+TqUkIXpQ0g2m+Wqq67i7rvvRpIkjj/+eB588EHsdvsh8ZAYGBhg586dCIJAa2vrtKunaF+M3sDsejllMhmCPTmHb5VSicVqnbatuyCKY0KIMxWnbFaky+sl2NNzoKWGYuZ/FwlQiLkUeUmhWNCOFXnH+O5uP/H4MCbTSGuOkpHMMZWCWqOOqqqcQIVCIXbv3k1paSlr1qxZdqnhc2Wq2qfh4WFcLhd+v5+amhqcTmfR2aeZTIannnqKm2++mWAwyJVXXsmll1665LVei40sTHPgZz/7Gb///e9577330Gg09Pf3L/WQePbZZ7nxxht55513+MxnPlMYW74l8qGCKIp0dHTgdrtxOp04HI4pV0994SEiPYNFv39ipENsT6gnVxBrtaLX63N7RpMgCBJSeuL9JEGpKITVimVwcJCOjk4UCoGmpmbKZ2SaKiFkxAM5DgoBSVG8OBaLKEqEw710d/vJZDJYrVZMJuOYzDGlUomlQY+2dGx6cyaTob29na6urqL+hocivb297N69G7Vajd1uJxQK0dPTg9lsxuFwFG30m0wm+c///E9uueUWkskk11xzDRdeeOGHTtCLRRamOfCjH/0IvV5PV1cXv/rVr5aFMN1+++2kUim++c1vUl1dTTKZ5Mc//jF33HEHmzdv5rvf/e4hlbYbjUbZuXNnwbF8qhs93DNAf3jqXk6DQ7kOsX19/dQYDFit1qJufgEJKZNlqmWJoBTGJSRMRzYr0t3tw+8PYLVaqK9vmHb1JDCxQAoKAXGexCmbyRZWkkqFAmtdHbW1tePGVlKixtxQjVo9eWg4Go2ya9cuJEli7dq1M3b+WO5EIhHa2toYHh6mvLycI444omjboOHhYR5++GFuv/12SktLue666/jHf/zHZe/MsNDIwjQPPPzww1x55ZXLQpgmQpIkXnvtNTZu3IjRaGTbtm00Nzcv9bCKJpvN0tHRgcfjoampaYxj8sGEAlEG+sb2cpKQiERyBbHD8WFMxpGC2CISP/Lee8XWBM1GnABiQzE6OjsQRYnm5qZJBViQpCmLiWcaVjyYVCqdW0n2BCnVlmKtq6O6Wj9hCLhCV4rRUlVUGFIURTweD+3t7dTV1bFixYpl7z4wFfns1s7OTgYGBmhoaMBoNNLR0VFU7VM0GuWBBx7grrvuwmq1snnzZv7u7/7ukJo0LiSyMM0Dy12Y8gwODnLttdfy2GOP8fOf/5wLLrjgkAqt9Pf3s3PnTtRqNa2trZOudILd/QxF42RFkdDIrF+UxFxBrNE0o5v/4P2kol6jUiDNQhlEUcLv9+Pz+TCbTDQ0Nh4wf5VAkMSiTFhzLeKFGYlTPB7H7w/Q29tLlU6Hta5u0l5RIFBjrEBfM7N+VJBbIbS1tTE0NMTq1asxmeYhO3ERybs0dHZ2Eo/HCy4NeZEdXftUWVnJ6tWrx9Q+hUIh7rnnHu6//37WrFnD5s2bOfvssw+p+3AxkIVpHjhUhAlyN86zzz7LN7/5TdavX8/dd9+NxWJZ6mEVTTabpb29Ha/XS3Nz84QJHYlEgnff3IXH5aNEW4LVYsVQY0AhzPDmz0zuyzcdsxUnyIlER3sH6Uwap7OJqiodQiY7o5rZYve8hoaG6O72098/Etqsq5syzVuhUGCu11NWPvsyg/zDe8+ePej1elavXl20H9xSIYoigUAAl8tFJpPBbrdTX18/6SQnX/u0bds21Go13/72t7n//vt56KGHOOGEE7j++us55ZRTZEGaBFmYDmLTpk3cdNNNUx7T1tbG6tWrC/8+lIQpTzgc5rLLLuP555/n9ttv54tf/OIhNXOdaPU0NDSE2+0mEAhQra9Gq9ajUWunTGiYEEmC7NT7ScUgqJSzblGe77ja5fFg0Fdja7TNOMwjqASkCcQ437ywu9tPLDaUC21arQcy7CZBrVFhbahGrZmfcFMqlWLv3r309PSwYsUKGhsbl901mG/34nK5EAQBh8NBXV1d0UWx//Ef/8HVV1/N4OAgJ5xwArfccgvHH3/8svucyw1ZmA4iFAoRDoenPKapqWnM5uShKExw4Mb5zne+wxlnnMHNN988q4Z+S0U2m2Xfvn34fD60Wi2JRAKr1YrNZqOiooJsVsTvicywl1Nx4bJiEdTKWdf/ChIkYsN0dHYQj8dzdTD6mf19RouTKEpEImG6u/2k02ksFgtmc3GhzfIKLUZr1az7Sk1F3tVbo9GwZs2aohMHFpLRLg0ajQan04nJZCpakHbt2sXNN9/Mb37zGz7/+c9jt9u57777+NznPsfNN9+M2WxehE9x6CIL0zxwqApTHq/Xyze/+U127tzJvffey8c//vFlP6PLh1bcbjeJRAKAsrIyjjjiiDEx/WxGxOcJk562l5OUsxaa97tBQlCpZrZyOmg/SSK3r+Fxe9Dr9dgd9gkLfydDFCR6RrrpCoKA1ZrLsCtWZKprKjAYF1YsRie42Gw2mpqalqQIPJVKFVqXl5eX43Q6i/Y4lCSJt99+my1btvDHP/6Rc889l+9///usWLECQRDw+Xx873vf41Of+hTf+MY3FuHTHLrIwjQHPB4PkUiEp59+mi1btvDKK68AsGLFiqLrF5YLoihy7733smnTJr7+9a/z05/+dFnWUKTTabq6cq24lUoldrsdq9UKwL59++ju7h4XFspksvhcYTJT9HKay37S9EigUhUfGcyIE5qwplJJXC4Xg4NDOBwODDWGKcOU6Uwuwy4YCFJaXoalvh6DofieWoIgYLJWUaFbPGuhwcFBdu3aRTqdZu3atRgM89s2ZDISiQRutxufz4der8fhcMzIpeHVV19ly5YtvPHGG1x44YVcc801NDY2Tni8JEnLfuK31MjCNAcuuOACHnnkkXE///Of/8ypp566+AOaB/bs2cMFF1xAOBzmgQce4CMf+ciyuIni8Thut5vu7m4qKysndUKPRCLs3LmT0tJSWltbC5Y/6VQGnzs8rpdTrj5pcdpmTBfWmy4VHEZS38MRXC4XlZUVIy01xiYiJBIJ/AE/oVAIXaWOujorlTodihms3FRqJZb6akqWwIQ1b/uzf/9+zGYzK1euXLC6nlgshtvtxu/3U1tbi9PpLNrQWBRFnnvuOW6++WZ2797NJZdcwpVXXonJZFqQsR5OyMIkM45MJsMvfvELbrzxRr773e9y3XXXLVnBX39/P263m1AohMlkwm63T2vPkslk2LdvH36/n5UrVxbsYpKJNN2eMGJWWpD9pGKYLCGiGFEaTTqTxu1y09/fj81uw2g0MhwbptvfTV8kgsFQQ12dlbKysaveYhIySss0mOuqUc6xnftcSSQStLW1EY1GaWlpwWKxzNskaXBwkM7OTkKh0IxdGjKZDL/5zW/YunUrgUCAK664gssuu+xDVzi8lMjCJDMpb731Fueffz4lJSXcf//9rF27dlHOm68VcbvdDA4OUl9fj81mm7HhaTgcZteuXZSVlbF27VpKS0tJxFP4PRHEdHZBexZNySiXBEmaWQHvwUT6InR2dCJJEqIkYjKasFqtUxYPTyVOVdXl1Jgql8UqGXLXQk9PD7t3756wLmim9Pf309nZSSQSob4+1+K92OsqlUoVbIPi8ThXX301F1100bIMeR/qyMIkMyWJRILrr7+e++67jxtuuIFLL710wTal86m5brcbURSx2WzU19fPySEgk8mwd+9eAoEAq1ator6+nkQsid/Vu2S6hADkEw9mmXAhSiJ9kT66/d2kkik0JZpcwWejDbPFPG2K/PiwooDJqqNymTb1S6fT7Nu3j0AgQFNTEzabregaoHxHYZfLxcDAAI2Njdhsxbd4Hx4e5pFHHuH2229Hq9Vy7bXXct555y2bljELicvl4qc//Sl/+tOfCAQC1NXVce6553L99dcvaBRFFiaZaZEkiZdeeomNGzfS2NjItm3bsNvt8/b+yWQSr9dLV1cXWq0Wu91edAO1Yunt7WXXrl1UVFSwdu1asimJoCe8pOIkMPNFmyhm6ekJ4Q/4ERCwWq0YjbUoFEoGBqJ0dHSi0ahxNjVN2EPqANKIOAmTmrAuR/r6+mhra0OhULBmzZopw7r51VZnZyeJRGKcS8N0DAwMFGyDzGYzmzZt4itf+cphZRv03HPP8fjjj/MP//APrFixgh07dnDRRRfxj//4j2zdunXBzisLk0zRRKNRrrrqKv77v/+bm266ia9//etzEo/RBbEGgwG73V50JtRsSKfThYLOVatWUVlaRcjXvyDnmgoBCTGTQVAIoFBSTLpeOpMmGAgSDAbRlGios9ZRbage52Yhilm83i6CPUEa6uuxWK1TOF5IlFSWYmmoRqVafv25JmN0366Ghgaam5vHiMXBLg0Oh4P6+vqiV/q9vb3cc889bNu2jZaWFjZv3sxnP/tZ2aVhhC1btnDvvffS0dGxYOeQhUlmRkiSxG9/+1u+9a1vcdxxx3HnnXfOKAspb37pdrvp6+vDYrFgt9sXNb0+FAqxa9cudDoddaZGhiKJRTmvhIRCEhFH7ScJCgUoFEwmTslkEr/fT0+oh8rKSuqsdeiqdNOG6gaHBuns6EBQKGhuahqXBAFQWV2GsX7hJgILTSwWY9euXSQSCVavXo3BYMDn8+F2u1EoFDgcDqxWa9GC0t3dze23385DDz3E8ccfzz/90z9x2mmnyYJ0ED/4wQ947rnneOuttxbsHLIwycyKnp4evvWtb/Haa69x55138pnPfGbKB9zogthkMrnkrd3T6TR79uwhFAphqalHTekCP6AlEEUkcaJ2FYpcL6VRYjM8HKO7208kEqbaYKDOWjfjTXZREvH5fPj9fqxWK/X19ShGnMdrLHqqag+tWruJkCQJj8fD/v37ASgtLaW5ubloc1hJkujs7OTWW2/lscce45Of/CSbNm1iw4YNh6xgLyT79+/nmGOOYevWrVx00UULdh5ZmGRmjSiKPProo1x55ZV87nOf46abbhoX80+n0/h8PjweD0qlEpvNRl1d3bJp7d7T00NbWxtCWoXRYEWjXoh9FgkpM7XzhKDIOYIPjbQtHxgcKLTnmKvB6fBwjPaODiRRZMXKFaxYa6e0YnmbphbDaJeGsrIyFAoFg4ODhSSXqYRFkiTa2tq4+eabeeqpp/jiF7/Iddddx/r16w8LQZqNJ6jP5+OUU07h1FNP5cEHH1zQ8cnCJDNnXC4XGzdupKOjg23btvGxj32s0HY6kUhMWRC7HEilUuzZs4fOPV7MNXXU1NTM2zgFRMRpXCUkCfoiEfzBAIl0GovZgtlinpHt0HSIkkhvJMRgIoLdaWPFihXLZnIwUxKJBC6XC5/PR3V1dc5DcMTjMd/SXavVsnbt2nGrTEmSeOedd9iyZQvPP/88X//61/n+97/PypUrl+W1uVDM1BO0u7ubU089lRNOOIGHH354wcObsjDJzAvZbJY77riDf/qnf8JsNuPz+di0aROXXnrptAWxy4VgMMhfX3oLjao056gwh9WThJQrms1OLkpiViTUG8Lv9yNJYLVaMFksKOdRkPKU67SYGg3E43F27dpFMplkzZo11NTUzPu5FopYLIbL5SIQCGA0GnE4HBO6NIxu6d7X18fZZ5+NVqst2Aa9/vrrBdsgm822BJ/k0MLn83HaaadxzDHH8Otf/3pRJjSyMC1j7r77brZs2UIgEGD9+vXceeedHHfccUs9rHGIosjvfvc7br75Zt566y3Ky8uprKzk3/7t3zj66KOXengzIplM8pc/v0ko0IvD4aCmpnYW7zL5fhLkHpzBYJBgIIharcZaZ6XGUJPL0gMUSuWE7Spmi8Gso9p04AEuSRJdXV3s27cPi8XCypUrl3U32YGBAVwuV24/0GLB4XAUtd/W19fHJz/5SXp7ezEajfh8Pr797W/zve99T3b3LhKfz8epp56K3W7nkUceGSNKC9nHTU43WaY8/vjjXHXVVfzoRz/inXfeYf369Zx55pn09PQs9dDG8dJLL3HppZdy9tln4/P56O7u5txzz+WTn/wkN910E+l0cW0nlgMlJSWccsaJtKxZhcvlYt++fTMavzCynzSRKKWSKdxuN++++x4D0QGamptYd8QROffqUU39xGwWYR7miwqlgMVeM0aUIGfO2tjYyIYNG0gkErz++uuEQqE5n2++6evr45133uHNN99Eo9Fw4oknTtm5eDTZbJY///nPqNVqhoaG2LdvH1/60pfYvHmzLEoz4Pnnn2f//v288MILNDQ0YLVaC/8tJPKKaZly/PHHc+yxx3LXXXcBuVVJY2Mjl19+OZs2bVri0Y1FkiTS6fSYSnBJknjjjTc4//zzqaqq4v7772fVqlVLOMqZkc2KuPf42LN7H4MDAzidTgyGqcNe+fqkg4kPx+n2dxMJR9Dr9VjrrEWlxytUKqRZNitUa1RYHDVoSqZeCUlSrp37nj17qK2tpaWlZcl8EfPjCYfDdHZ2MjQ0VHBpKHZMqVSKxx9/nFtuuYVYLMZVV13FxRdfTDAY5JJLLmHHjh385S9/weFwLOwHkZkTsjAtQ1KpFGVlZTz55JN84QtfKPz8/PPPp7+/n9/+9rdLN7gZEovF2LRpEw8//DA/+clPuOiiiw6ZupBsJouvvQd/dxC320VVlR673T4u7JWrT5IQR+0nSRK5DDt/NwPRAWpra7FYrZSWziwbbjbiVFpRgtlWM6Omfslkkt27d9PX18fq1asxm82LmgyQ79jrcrlIJBLY7XYaGhqKDjHG43EeffRRbr/9dlQqFddeey0XXHDBmHIESZJ49tlnOeussw6rRIdDEVmYliHd3d3U19fzl7/8hQ0bNhR+/v3vf5+XXnqJN954YwlHN3MkSeL555/nwgsvpKWlhXvvvZf6+vqlHlZRpFMZujtCDA/HcY3M4h1OJ4bqfJ8gCcQskjjS1E+C/r6ch108HsdstmAxm1FrZr+Ho1CrkIrsV6GvrcBgqZrVg3e0YWpVVRWrV6+ec6r6dIiiiN/vx+VyIYoidrt9Ri4NAwMD/OpXv+LOO++ktraWTZs28dWvfvWwsg36MCL/9WQWHEEQOOOMM9i+fTvf/e53Oe6447jlllv4yle+suxnrmqNCquzlu6OECtXriIcDtPR3kFfdQSH3Y4i53iHJOYc0f0BP2JWxGK1YjIZ5yWDSUxnpl05CQoBY301lfrZm7AKgoDZbKa6upq9e/fy+uuvs3LlymlrgmZDNpvF5/PhcrlQKpU4nU4sFkvRq+lwOMy9997Lvffey8qVK7n33nv5/Oc/f8isxmWmRhamZUiu7bWSYDA45ufBYHBBM2EWmurqah599FGefPJJLrnkEp555hluu+22ZZ+yrClRY3XU0t0Zora2Fp2uks6ODt59+20cDgfJRJJAIIBKpaKurp7ampoxyQzzgZiZXJxUGiUWWw0l82TCqtFoWLduHaFQiLa2NoLBIGvWrJlTu4k86XQar9eLx+NBq9XS0tJStEsDQCAQ4Pbbb+df//Vf+chHPsJ//dd/8YlPfEIWpA8Z8l9zGaLRaDjmmGN44YUXCj8TRZEXXnhhTGjvUEQQBM455xw++OADEokExx13HM899xzLPaJcUqrBYq9FUECJWo29sZHy8nL2799PIBDAZrdxxJFHYjTWzrso5cklVoz9nrTlGuqbTPMmSqMxGo2ceOKJlJWV8de//hWPxzPrv1MymWTfvn288sorRCIRjjjiCI4//vii9rLytkFXXHEFra2ttLe38+yzz/KnP/2JT37yk7IofQiR95iWKY8//jjnn38+27Zt47jjjuO2227jv/7rv9i9e/eHJt1VFEUefPBBrrnmGs455xxuvPHGRTVznQ09/hDv/WU74d4wVVVVGI1Ggj1B4sNxnE3OReliKqhVIAlUGsox1ukXJRwaiUTYtWsXGo2GtWvXFv13isfjuN1ufD4fBoMBp7P470iSJHbv3s0tt9zCf//3f/P5z3+e6667jqOPPnrZh4Dnm5/97Gf8/ve/57333kOj0dDf37/UQ1pQZGFaxtx1112FAtujjjqKO+64g+OPP36phzXv7N+/n40bN+Lz+bj//vuXpYFmf38/LpeLcDhMVZkeLWWFxABJglBPD26Ph9qaGmx228JWxwsCxsZaqmoWV8Sz2Szt7e14vV6cTicOh2PS1crQ0BAul4tgMIjRaMTpdFJZWVnUeSRJ4r333mPLli0899xzfO1rX+P73/8+LS0ty+66WCx+9KMfodfr6erq4le/+pUsTDIyi0E2m2Xr1q385Cc/4dvf/jY/+MEPlrxDqCRJ9Pb24nK5GBoaKjiia7VaBnoH6fH2jjk+mUzS0ZFrStfU5FwQKyalSonZYaSscmZt5ueTaDTKzp07USgUrF27dowtUDQaxeVy0dvbi9VqxW63F+2KLkkSr732Glu3buW1115j48aNXHPNNXLN0SgefvhhrrzySlmYZGQWk/fff5/zzjsPSZJ44IEHOOKIIxZ9DKMbzaXT6UIK88E1Nf3BKL3dkTE/W8jVU0lpCZYmE2rN0ucsjW7W19jYiMFgwOPx0NfXR0NDA3a7vehUc1EU+eMf/8jWrVv54IMPCrZBh3Kiz0JxuAjT0l/hMjKjWL9+PX/729/40Y9+xMc//nE2b97Md7/73UWpS8lkMnR1dRVadEzXaE5vriIrivQF+gs/EwQwmU1U6avoaO9g+/YPaG5qQlc13mx0JlToyzHZa5fNRr9CoaCpqQm1Ws3+/ftxu93U1dXxsY99rGiXhmw2y9NPP83WrVvxer1897vf5emnn8ZgMEz/YpkPNfKKSWZZkg/rXHDBBZjNZrZt20ZTU9OCnCuZTOLxeOjq6qK8vByHwzGjFh2hrjDR0MC4n0sS9PQE8Xi8GI21NDY2zmr1VFNXTbVZP+PXLRSiKBZcGlKpFDabDVEUcblc1NfXs2LFiiknEul0umAbNDg4WLANKnYP6sPCbHoiHS4rJlmYZJY1g4ODXHvttTz22GPceOONnH/++fO2aojFYrjdbvx+PwaDAYfDgV4/uyy3oDvEYGRowt8lEgk62jtIpVM0NzVTqSvuAaxQKjDbjZRXzb1+aD4QRZHu7m5cLheSJOFwOMY0fRzd6nzt2rXj6tPi8Tj/9m//xu23345CoSjYBi20u8RyZaY9kUAWJhmZZYMkSfzhD3/goosuYv369dx9991z2n8YvUFvNptxOBxzTlOXJIlAZw+x6PAkv4dgMIDX24XJZKSxoRHFFF52mhI1liYTGu3SGarmyWQy+Hw+3G43KpUKp9OJ2WyecIKQb6mxd+9eXnnlFS677DK0Wm3BNshgMBRsg5Zzq43liixMMjLLjN7eXi677DJeeOEFbrvtNr74xS8WvbrJu1a7XC4GBgaor6+f0QZ9sefo3h8kPhSf9Jh4PEFHRzvpdJrm5hVUVo4XxHJdGSaHcUYmrAtBOp0utC4vLS3F6XQWHeIMh8N88YtfZNeuXSgUCtasWcPmzZv5/Oc/f8h2zl1KPB4PkUiEp59+mi1btvDKK68AsGLFimVf+zcbZGGSOaSQJInHHnuMyy+/nDPPPJOtW7cW2mpPxET7ITNxrZ4poijSvS9AYjg56TGSlLPW6fJ6MZvNNDQ0FFZP1eYqauqWdvM/mUzidrvp6uqiqqoKh8OBwWCYkW3QHXfcwa9+9SusVit+v5+zzjqLu+66C5PJtMCj/3BywQUX8Mgjj4z7+Z///GdOPfXUxR/QAiMLk8whidfr5cILL6StrY17772X0047bcyDM5PJ0N3djdvtRhCEQobdYszWs1kR314/qURqyuPyq6dMJsOKFStoWuug0rB0s9/h4WHcbjfd3d3U1NQU9tyKQZIk3G43t912G7/+9a859dRT2bx5MyeddBLBYJDvfOc7vPLKK+zdu3dB6rtkPlzIwiRzyCKKIvfccw+bN2/m3HPP5ac//Sl9fX28+OKL1NXVUVZWhsPhmJFJ6HyRSWfw7Q2QTk3d/VaSINTbw0Cmn+aVTTQ1NS16qGu0S4PJZMLpdBYdHpIkiT179nDLLbfw5JNP8tnPfpZNmzbx//7f/xv3nW/fvp0jjzxyIT6CzIcMWZhkDnn27NnD3//939PZ2Uk8HufUU0/lX//1X6murl5SC5t0KoNvbzeZdHbSY7TlWqxNJuKJODt37iSbzdLa2rooq4poNEpnZyfhcBir1YrD4SjaQVySJN5//322bNnCs88+y1e/+lWuu+46Vq9efdjaBsnMH8ujWk9mWfDyyy/z2c9+lrq6OgRB4De/+c1SD2la3n77bW644Qba2tqw2+0IgsAxxxxDRUXFkj8g1RoVdSssKFUTr4CqanXUr8z9vqKigmOPPRar1cpbb73F/v37EUVx3sckSRKRSIS3336bt99+m7KyMj760Y+ydu3aokRJkiT+8pe/8KUvfYnTTz8dq9VKW1sbDz30EGvWrFny71zmw4EsTDIFYrFYIR37UCCTyfC1r30Nq9XK3r172b59O6+99hpPP/00H//4x2lra1vqIaLRaqhrNo9JDRcEAVNjLcbGmjEPcoVCgdPp5LjjjqO3t5c33niDgYHxhbuzId+d9s033+T9999Hr9dz0kknsWrVqqIyE/O2QZ/61Kf40pe+xJFHHkl7ezv33HMPTqdTFiSZeUUO5clMiCAIPPXUU3zhC19Y6qFMSTabHbcnE4/Huf7669m2bRs33HADl1566ZKnKMeHEvjbgyiUAmaHidKKqcUg76TQ2dmJw+HA6XTOqrA4n5XY2dlZ8P1raGgo2uIpm83yzDPPsHXrVlwuF5dffjnf/e53P/S2QXfffXfB2X/9+vXceeedHHfccUs9rMMGWZhkJuRQEabJkCSJl156iY0bN2Kz2bjvvvuw2+1LOqbhwTjqEvWMTFgHBwfZsWMHAOvWrSvatiebzRayEoEZZyWm02meeOIJbrnlFvr7+/ne977Ht7/97cPCNujxxx/nvPPO47777uP444/ntttu44knnmDPnj1yuvsiIQuTzIQc6sKUJxqN8r3vfY//+Z//4Ze//CVf+9rXlo0RarGMdvKerg9S3ojW7Xaj0WhwOByTujRMRCKR4Ne//jW33norgiBwzTXXsHHjRkpLl67NxmJz/PHHc+yxx3LXXXcBue+/sbGRyy+/nE2bNi3x6A4PZHdxmQ81VVVV/OpXv+Jzn/sc3/rWt3jmmWe44447DqmZr0KhoLm5GaPRyM6dO+np6WHdunVjUrpTqRRerxePx0N5eTlr166ltra26L2foaGhgm2QXq/nxz/+MV/72tcOO9ugVCrF22+/zebNmws/UygUnH766bz++utLOLLDi0Nr6igjMwsEQeALX/gC27dvR6FQcPzxx/PMM89wqAULdDodxx9/PLW1tbzxxht0dnYyPDzMnj17ePXVV+nv72f9+vUce+yxRVsH9fX1ceONN7JmzRqefPJJ7rjjDj744APOP//8w06UIGd7lc1mMZvNY35uNpsJBAJLNKrDD3nFJHPYYDab+Z//+R8effRRLr74Yj7/+c/zi1/84pByIlAoFKxYsYLKykp27drF/v37MRgMHHPMMTP6HIFAgLvuuosHH3yQo48+ml//+teceeaZh1yYU+bDiXwVyhQYGhrivffe47333gOgs7OT9957D4/Hs7QDm0cUCgUXXHBB4XOdcMIJvPzyy4fM6mlwcJAPPviAHTt2UFtbS11dHf39/fT19U37GfK2QVdddRXr1q2jra2NZ555hhdffJGzzjpLFiWgtrYWpVJJMBgc8/NgMCh31F1E5CtRpsBbb73F0UcfzdFHHw3AVVddxdFHH80NN9ywxCObfxwOB3/84x+54oor+PKXv8zmzZuJxyd3BV9q+vv7effdd/nb3/6GSqXixBNP5IgjjqC1tZVjjjkGn8/Hm2++SSwWG/favG3QJZdcwtFHH00oFOLll1/mD3/4AyeffLJcgzQKjUbDMcccwwsvvFD4mSiKvPDCC2zYsGEJR3Z4IWflyRz27Ny5k/POO49EIsEDDzzAUUcdtdRDAg64NHR2djIwMEBjYyM2m42SkpJxx2azWdrb2/F6vSQSCc4880yUSiXbt29n69at/P73v+crX/kKmzZtkh0apuHxxx/n/PPPZ9u2bRx33HHcdttt/Nd//Re7d+8et/ckszDIwiQjQy4b66c//Sk333wz1157LVddddWSbf5LkkQoFCp4/9lsNhobG4saT29vL6eccgoKhQKr1co777zDeeedx/e//33ZoWEG3HXXXYUC26OOOoo77riD448/fqmHddggC5OMzAiSJPHGG29w/vnno9fr2bZtG6tWrVq084uiSCAQwOVykclkCi4NxRbFiqLIn//8Z37xi1/wt7/9DUEQuP766/nhD38o7x/JHFLIV6uMzAiCIHDCCSfwzjvvcOyxx3LSSSexbdu2BTFTHU02m8Xr9fLaa6/R0dGBzWbjpJNOwm63FyVK2WyWp59+mlNPPZXzzz+fT3ziEwQCAZ5//nkeffRRTjvtNMLh8IJ+BhmZ+UReMcnITIAkSTz//PNceOGFtLS0cO+991JfXz+v58hkMoWiWI1Gg9PpxGw2Fx1uS6fTPPnkk9xyyy1EIhGuvPJKLrnkEnQ6XeGYoaEh7rvvPr73ve8tuV+gjEyxyMIkIzMFfX19XH755fz+97/nlltu4Stf+cqc92lSqRQejwev10t5eTlOp3NGLg2JRIJ///d/59Zbb0UURa655hq+8Y1vFN1LSUZmuSMLk4zMNEiSxBNPPMGll17Kqaeeyq233kpNTc2M3yeRSOB2u+nq6qK6uhqn04ler5+RbdC//uu/cuedd1JZWcl1113Hueeee1g6NMh8uJGFSUamSLq7u7nooot45513uPvuuznzzDOLEpVYLIbL5SIQCFBbW4vT6RwTbpuOvr4+tm3bxj333IPNZmPTpk18+ctflkNzMh9aZGGSkZkBoijy4IMPcs011/CVr3yFn//852PMVEczODhIZ2cnoVAIi8WCw+GgvLy86HMFg8GCbdCRRx7Jpk2bZIcGmcMC+QqXkZkBCoWCiy++mHfeeYfdu3ezYcMGXn/99TF2QKNdGjQaDSeeeCKtra1Fi5LH4+Hqq69m3bp17Nixg9/+9re8/PLLnH322R9qUXr55Zf57Gc/S11dHYIg8Jvf/GaphySzRHx4r3IZmQVkxYoVvPjii1x88cV87nOf44YbbuDxxx/n5JNP5o9//CMVFRWcdNJJrF69uqheRpIksW/fPi655BKOOuoogsEgf/7zn3nuuec49dRTD4vC2Fgsxvr167n77ruXeigyS4zsLi6z5Nx44438z//8D7t376a0tJQTTzyRm266iZaWlqUe2pSoVCquueYalEolN9xwA8lkkq9+9aucdtppRSdHSJLEjh072LJlC8888wznnHMOb731Fq2trYeFGI3mrLPO4qyzzlrqYcgsA+QVk8yS89JLL3HZZZfx17/+leeff550Os0ZZ5wxoSHpcuKpp56itbWV22+/nX/5l3/hiiuu4De/+Q2PPvoomUxmytfmXSbOOeccTj31VGpra9m5cyePPvoo69atO+xESUZmNHLyg8yyIxQKYTKZeOmllzj55JOXejiT8sQTTzA4OMi5556LRqNBkiReffVVNm7ciMVi4b777qOpqWnMa0RR5KWXXuKXv/wl77zzDhdddBFXXXUVDQ0NS/QplieCIPDUU0/xhS98YamHIrMEyCsmmWVHNBoFwGAwLPFIpuacc87hG9/4BhqNBsg9TD/2sY/x7rvv0trayoknnshDDz2EKIqIosgzzzzDaaedxj/+4z9y8skn09nZyS233CKLkozMQcgrJpllhSiKfO5zn6O/v59XX311qYczayRJ4g9/+APf/OY3sVgsxONx+vv7C7ZBh1LX3KVAXjEd3sjJDzLLissuu4wdO3Yc0qIEuQfr2WefzQcffMCGDRv4/Oc/z09+8hPZNkhGpghkYZJZNnznO9/hmWee4eWXX/7QhLdqa2vZt2/fUg/jkGBoaIj9+/cX/t3Z2cl7772HwWDAZrMt4chkFhs5lCez5EiSxOWXX85TTz3Fiy++yMqVK5d6SDJLwIsvvshpp5027ufnn38+Dz/88OIPSGbJkIVJZsm59NJLeeyxx/jtb387pnapqqqqqOJUGRmZDxeyMMksOZPV7Dz00ENccMEFizsYGRmZJUfeY5JZcuS5kYyMzGjkOiYZGRkZmWWFLEwyMjIyMssKWZhkZGRkZJYVsjDJyBzm3HjjjRx77LFUVlZiMpn4whe+wJ49e5Z6WDKHMbIwycgc5hyq7u4yH17kdHEZGZkxHCru7jIfXuQVk4yMzBgOFXd3mQ8v8opJRkamwIfF3V3m0EYusJWRkSnwYXF3lzm0kYVJRkYG+HC6u8scmsjCJCNzmHOwu7vT6VzqIckc5sjJDzKHNffeey9HHnkkOp0OnU7Hhg0bePbZZ5d6WIvKZZddxq9//Wsee+wxKisrCQQCBAIB4vH4Ug9N5jBFTn6QOaz53e9+h1KpZOXKlUiSxCOPPMKWLVt49913aW1tXerhLQqyu7vMckMWJhmZgzAYDGzZsoULL7xwqYciI3NYIu8xyciMkM1meeKJJ4jFYmzYsGGphyMjc9giC5PMYc8HH3zAhg0bSCQSVFRU8NRTT7F27dqlHpaMzGGLHMqTOexJpVJ4PB6i0ShPPvkkDz74IC+99JIsTjIyS4QsTDIyB3H66afT3NzMtm3blnooMjKHJXK6uIzMQYiiSDKZXOphyMgctsh7TDKHNZs3b+ass87CZrMxODjIY489xosvvsj//u//LvXQZGQOW2Rhkjms6enp4bzzzsPv91NVVcWRRx7J//7v//LJT35yqYcmI3PYIu8xycjIyMgsK+Q9JhkZGRmZZYUsTDIyMjIyywpZmGRkZGRklhWyMMnIyMjILCtkYZKRkZGRWVbIwiQjIyMjs6yQhUlGRkZGZlkhC5OMjIyMzLJCFiYZGRkZmWWFLEwyMjIyMssKWZhkZGRkZJYVsjDJyMjIyCwr/j8j/QRJrNny/AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.scatter(X_test[:, 0], X_test[:, 1], y_pred, alpha=0.3)\n",
    "ax.view_init(30, 50)\n",
    "x1_range = np.linspace(X_test[:, 0].min(), X_test[:, 0].max(), 10)\n",
    "x2_range = np.linspace(X_test[:, 1].min(), X_test[:, 1].max(), 10)\n",
    "X1_grid, X2_grid = np.meshgrid(x1_range, x2_range)\n",
    "\n",
    "intercept = model.intercept_\n",
    "coef1, coef2 = model.coef_[0], model.coef_[1]\n",
    "Z = intercept + coef1 * X1_grid + coef2 * X2_grid\n",
    "ax.plot_surface(X1_grid, X2_grid, Z, cmap='viridis', alpha=0.2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9932ce8",
   "metadata": {},
   "source": [
    "## 自动选择 `alpha` 取值\n",
    "\n",
    "`sklearn` 内置使用 AIC（赤池信息准则）或 BIC（贝叶斯信息准则）等统计指标，选择准则值最小的 `alpha` 的算法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5e116dc6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "系数\t[-85413.28005747 -90669.13624699  14885.95835764 -17862.58294108\n",
      "  48973.14892415 -43589.91735845  17717.71485854  77013.87535191]\n",
      "截距\t206763.77475721933\n",
      "R2评估\t0.6246548578993617\n",
      "MSE\t4918556441.477828\n"
     ]
    }
   ],
   "source": [
    "model_ic = LassoLarsIC(criterion='bic')\n",
    "model_ic.fit(X_train, y_train)\n",
    "\n",
    "print(f'系数\\t{model_ic.coef_}')\n",
    "print(f'截距\\t{model_ic.intercept_}')\n",
    "print(f'R2评估\\t{model_ic.score(X_test, y_test)}')\n",
    "\n",
    "y_pred = model_ic.predict(X_test)\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "\n",
    "print(f'MSE\\t{mse}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80c3f001",
   "metadata": {},
   "source": [
    "R2反而变小了，MSE反而变大了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "10adc43c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.0)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_ic.alpha_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2934b845",
   "metadata": {},
   "source": [
    "破案了，这个IC没啥用，事实上，当alpha=0，这就是线性回归"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fe62600",
   "metadata": {},
   "source": [
    "## 网络搜索分析最优惩罚项系数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ed88d360",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alphas = np.logspace(-2, 3, 20)\n",
    "\n",
    "train_scores, valid_scores = validation_curve(\n",
    "    Lasso(), X, y, param_name=\"alpha\", param_range=alphas, cv=5, scoring='r2'\n",
    ")\n",
    "\n",
    "# plt.subplot(2, 1, 1)\n",
    "plt.title('Validation Curve for Lasso(r2)')\n",
    "plt.semilogx(alphas, np.mean(train_scores, axis=1), label='Training score')\n",
    "plt.ylabel('Score')\n",
    "plt.legend()\n",
    "# plt.subplot(2, 1, 2)\n",
    "plt.semilogx(alphas, np.mean(valid_scores, axis=1), label='Validation score')\n",
    "plt.xlabel('Alpha (Regularization strength)')\n",
    "plt.ylabel('Score')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8ffa9fae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alphas = np.logspace(-2, 3, 20)\n",
    "\n",
    "train_scores, valid_scores = validation_curve(\n",
    "    Lasso(), X, y, param_name=\"alpha\", param_range=alphas, cv=5, scoring='neg_mean_squared_error'\n",
    ")\n",
    "\n",
    "# plt.subplot(2, 1, 1)\n",
    "plt.title('Validation Curve for Lasso(-MSE)')\n",
    "plt.semilogx(alphas, np.mean(train_scores, axis=1), label='Training score')\n",
    "plt.ylabel('Score(train)')\n",
    "plt.legend()\n",
    "# plt.subplot(2, 1, 2)\n",
    "plt.semilogx(alphas, np.mean(valid_scores, axis=1), label='Validation score')\n",
    "plt.xlabel('Alpha (Regularization strength)')\n",
    "plt.ylabel('Score(test)')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c73a320d",
   "metadata": {},
   "source": [
    "## 结果分析\n",
    "\n",
    "训练集的评价比验证集高出很多，这表明模型泛化能力有差距，可能是过拟合了。  \n",
    "下面通过学习过程分析，看看学习过程中 MSE 的变化。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fc64dac",
   "metadata": {},
   "source": [
    "## 学习过程曲线分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "52ac40a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 生成学习曲线数据\n",
    "model = Lasso(0.1)\n",
    "cv = ShuffleSplit(n_splits=10, test_size=0.2, random_state=0)\n",
    "train_sizes, train_scores, valid_scores = learning_curve(\n",
    "    model, X, y, \n",
    "    train_sizes=np.linspace(0.1, 1.0, 10),  # 从10%到100%的训练数据\n",
    "    cv=cv, \n",
    "    scoring='neg_mean_squared_error',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "# 计算均值和标准差\n",
    "train_mean = -np.mean(train_scores, axis=1)\n",
    "train_std = np.std(train_scores, axis=1)\n",
    "valid_mean = -np.mean(valid_scores, axis=1)\n",
    "valid_std = np.std(valid_scores, axis=1)\n",
    "\n",
    "# 绘制学习曲线\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.title('Lasso Learn route')\n",
    "plt.xlabel('Train sample size')\n",
    "plt.ylabel('MSE')\n",
    "\n",
    "# 绘制训练曲线\n",
    "plt.plot(train_sizes, train_mean, color='blue', marker='o', markersize=5, label='Train MSE')\n",
    "plt.fill_between(train_sizes, train_mean + train_std, train_mean - train_std, alpha=0.15, color='blue')\n",
    "\n",
    "# 绘制验证曲线\n",
    "plt.plot(train_sizes, valid_mean, color='green', marker='s', markersize=5, label='Valid MSE')\n",
    "plt.fill_between(train_sizes, valid_mean + valid_std, valid_mean - valid_std, alpha=0.15, color='green')\n",
    "\n",
    "plt.legend(loc='upper right')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d2a5988",
   "metadata": {},
   "source": [
    "训练集的方差越来越大，验证集的方差越来越小，说明确实没有过度训练，就是纯纯泛化能力差  \n",
    "但离谱的是。。。为什么训练集的方差比验证集大？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a3abe568",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 生成学习曲线数据\n",
    "model = Lasso(0.1)\n",
    "cv = ShuffleSplit(n_splits=10, test_size=0.2, random_state=42)\n",
    "train_sizes, train_scores, valid_scores = learning_curve(\n",
    "    model, X, y, \n",
    "    train_sizes=np.linspace(0.1, 1.0, 10),  # 从10%到100%的训练数据\n",
    "    cv=cv, \n",
    "    scoring='neg_mean_squared_error',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "# 计算均值和标准差\n",
    "train_mean = -np.mean(train_scores, axis=1)\n",
    "train_std = np.std(train_scores, axis=1)\n",
    "valid_mean = -np.mean(valid_scores, axis=1)\n",
    "valid_std = np.std(valid_scores, axis=1)\n",
    "\n",
    "# 绘制学习曲线\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.title('Lasso Learn route')\n",
    "plt.xlabel('Train sample size')\n",
    "plt.ylabel('MSE')\n",
    "\n",
    "# 绘制训练曲线\n",
    "plt.plot(train_sizes, train_mean, color='blue', marker='o', markersize=5, label='Train MSE')\n",
    "plt.fill_between(train_sizes, train_mean + train_std, train_mean - train_std, alpha=0.15, color='blue')\n",
    "\n",
    "# 绘制验证曲线\n",
    "plt.plot(train_sizes, valid_mean, color='green', marker='s', markersize=5, label='Valid MSE')\n",
    "plt.fill_between(train_sizes, valid_mean + valid_std, valid_mean - valid_std, alpha=0.15, color='green')\n",
    "\n",
    "plt.legend(loc='upper right')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "689f456c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 生成学习曲线数据\n",
    "model = Lasso(0.1)\n",
    "cv = ShuffleSplit(n_splits=10, test_size=0.2, random_state=88)\n",
    "train_sizes, train_scores, valid_scores = learning_curve(\n",
    "    model, X, y, \n",
    "    train_sizes=np.linspace(0.1, 1.0, 10),  # 从10%到100%的训练数据\n",
    "    cv=cv, \n",
    "    scoring='neg_mean_squared_error',\n",
    "    n_jobs=-1\n",
    ")\n",
    "\n",
    "# 计算均值和标准差\n",
    "train_mean = -np.mean(train_scores, axis=1)\n",
    "train_std = np.std(train_scores, axis=1)\n",
    "valid_mean = -np.mean(valid_scores, axis=1)\n",
    "valid_std = np.std(valid_scores, axis=1)\n",
    "\n",
    "# 绘制学习曲线\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.title('Lasso Learn route')\n",
    "plt.xlabel('Train sample size')\n",
    "plt.ylabel('MSE')\n",
    "\n",
    "# 绘制训练曲线\n",
    "plt.plot(train_sizes, train_mean, color='blue', marker='o', markersize=5, label='Train MSE')\n",
    "plt.fill_between(train_sizes, train_mean + train_std, train_mean - train_std, alpha=0.15, color='blue')\n",
    "\n",
    "# 绘制验证曲线\n",
    "plt.plot(train_sizes, valid_mean, color='green', marker='s', markersize=5, label='Valid MSE')\n",
    "plt.fill_between(train_sizes, valid_mean + valid_std, valid_mean - valid_std, alpha=0.15, color='green')\n",
    "\n",
    "plt.legend(loc='upper right')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c9c867e",
   "metadata": {},
   "source": [
    "看样子那个倒反天罡的图，应该是个个例。。。  \n",
    "实际上还是有轻微的过度训练的现象，大约在8000左右  \n",
    "然而 MSE 居高不下，估计得另想办法"
   ]
  }
 ],
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